Resident tests positive for COVID-19 at Barry Robinson Center – WAVY.com

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NORFOLK, Va. (WAVY) Officials with the Barry Robinson Center confirmed on Sunday that a resident tested positive for COVID-19.

The non-profit, behavioral healthcenterfor childrensaid that the resident is in isolation, doing well, and showing no symptoms.

Center officials also said that all residents staying in the same dorm have been seen by the facilitys pediatrician, tested for COVID-19, and results have come back negative.

Staff members who may have had direct contact with the resident have been notified and advised to follow VDH guidelines.

The center said that the facility is undergoing deep cleaning and sanitizing of the dorm.

Our number one priority is keeping our employees and residents safe. That priority focus guides our decision-making above all else, said staff with the center.

Since February, we have been andwill continue to follow the guidance of the CDC and other federal, state and local health officials. We have rigorous hygiene, infection-control and other practices in place to prevent the spread of COVID-19.

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Resident tests positive for COVID-19 at Barry Robinson Center - WAVY.com

As Covid-19 persists around the world, death is not the only outcome to fear – The Guardian

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There are a lot of unknowns about Covid-19. This makes sense, because despite six months of the most amazing scientific effort of our lifetimes, the coronavirus is a novel disease which means that we are constantly finding out new things about it. Even now, the debate about the most likely method of spread of the disease rages on, in part because the idea of masks has in many places become somehow a political decision rather than a scientific one.

Sometimes 2020 feels like living in the Bad Place (but with less frozen yoghurt).

But the worry about unknowns doesnt end at whether you should be sporting pandemic chic. One claim that has been flying around the airwaves, as we move from the early stages of Covid-19 to the endless ennui of an ongoing outbreak, is the idea that, since only a small proportion of people die from the disease, the rest of us should stop worrying about it and carry on. The idea is pervasive, and has been repeated worldwide since only 1% of people are going to be killed by the coronavirus, the 99% of us who arent going to die will be totally fine.

This is, unfortunately, completely off the mark.

Firstly, lets look at the facts. A colleague and I have looked into the infection-fatality rate of Covid-19, using data from dozens of studies, and our conclusion is that about 0.7% of people who catch the disease will die. So broadly speaking, saying that only 1% of people who get the disease will die isnt entirely wrong.

But theres a problem. Dying isnt the only issue that a disease can cause. Measles kills about 0.2% of people who catch it, but it leaves some people deaf, others with brain damage, and may cause permanent immune system damage to boot. Polio, the disease that causes terrifying paralysis, is entirely asymptomatic in upwards of 70% of people who catch it.

Similarly, the impact of Covid-19 cant be boiled down to a single number. For some, it causes death. For others, it causes lengthy ICU stays, which are themselves dangerous. Long-term mechanical ventilation, while hailed as the saviour of humanity early in this crisis, is associated with a host of serious health problems such as bacterial infections, ulcers and more. Even for those not admitted to ICU, there are worrying trends emerging indicating the potential for long-term organ damage such as kidney injury, or severe psychiatric issues.

Worse still, there are increasingly reports that these impacts are not wholly confined to people with severe infections. Some patients with mild symptoms are saying that they have had symptoms for weeks or months, a far cry from our usual ideas of mild disease. There is some evidence that symptoms like fatigue, which can be very long-lasting, are hitting people who barely had any issue earlier on in their affliction.

All in all, its not a pretty picture. Death may be the most easily identifiable outcome of coronavirus infection, but its certainly not the only one.

Which brings us back to that 99% figure. As the threat of a second wave looms, people are beginning to get tired of the ongoing government action. Wouldnt it be easier, they say to just let the disease roll through the population? Its only going to kill 1% anyway.

Perhaps, although its worth noting that in Australia and the UK a death rate of 1% would imply hundreds of thousands of deaths before the virus burned itself out. Moreover, those who are hospitalised a significant proportion of Covid-19 patients will certainly suffer. And even those with more mild disease may not be exempt from long-term harm. While government restrictions are starting to feel onerous, the fact is that we simply do not know enough about this disease to be sure that even the lowest risk is acceptable. Weve got a handle on short-term, acute issues the things that we see in a hospital but were still only just discovering what the long-term issues that this disease causes might be.

Unfortunately, the damage that Covid-19 causes is almost certainly not confined entirely to the death rate. We may not know for some time exactly what else it causes, but even now we have enough evidence to know that there are other problems out there. Letting everyone get infected is a strategy that, even ignoring the enormous death toll, could leave us much worse off as a society.

I wish I could end with an uplifting message, but really all theres left to say is simple: were in this for the long haul. I hate to be the bearer of bad news, but it seems like thats what 2020 is about for epidemiologists.

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As Covid-19 persists around the world, death is not the only outcome to fear - The Guardian

COVID-19 Daily Update 7-6-2020 – 5 PM – West Virginia Department of Health and Human Resources

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TheWest Virginia Department of Health and Human Resources (DHHR)reports as of 5:00 p.m., on July 6, 2020, there have been 188,875 total confirmatory laboratory results receivedfor COVID-19, with 3,442 total cases and 95 deaths.

In alignment with updated definitions fromthe Centers for Disease Control and Prevention, the dashboard includes probablecases which are individuals that have symptoms and either serologic (antibody)or epidemiologic (e.g., a link to a confirmed case) evidence of disease, but noconfirmatory test.

CASES PER COUNTY (Caseconfirmed by lab test/Probable case): Barbour(17/0), Berkeley (474/18), Boone (24/0), Braxton (3/0), Brooke (14/1), Cabell(161/6), Calhoun (2/0), Clay (11/0), Fayette (72/0), Gilmer (13/0), Grant(15/1), Greenbrier (66/0), Hampshire (42/0), Hancock (29/3), Hardy (44/1),Harrison (79/0), Jackson (145/0), Jefferson (240/5), Kanawha (346/9), Lewis(19/1), Lincoln (9/0), Logan (26/0), Marion (85/3), Marshall (43/1), Mason(21/0), McDowell (6/0), Mercer (57/0), Mineral (56/2), Mingo (20/3), Monongalia(285/14), Monroe (15/1), Morgan (19/1), Nicholas (14/1), Ohio (109/1),Pendleton (13/1), Pleasants (4/1), Pocahontas (30/1), Preston (73/16), Putnam(68/1), Raleigh (62/1), Randolph (169/2), Ritchie (2/0), Roane (11/0), Summers(2/0), Taylor (16/1), Tucker (6/0), Tyler (5/0), Upshur (20/1), Wayne (119/1),Webster (1/0), Wetzel (18/0), Wirt (5/0), Wood (124/8), Wyoming (7/0).

As case surveillance continues at thelocal health department level, it may reveal that those tested in a certaincounty may not be a resident of that county, or even the state as an individualin question may have crossed the state border to be tested.Such is the case of Monroe and Nicholas counties in this report.

Please visit thedashboard at http://www.coronavirus.wv.gov for more information.

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COVID-19 Daily Update 7-6-2020 - 5 PM - West Virginia Department of Health and Human Resources

US notes 62000 COVID cases in another record-breaking day – CIDRAP

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Yesterday US officials reported 62,751 new cases of COVID-19, setting yet another record in a summertime surge that has swept across much of the South and West.

Though Florida, Arizona, and Texas still lead in the number of new cases, Oklahoma and Louisiana are reporting spikes. And according to the Washington Post five statesAlabama, Iowa, Missouri, Montana and Wisconsinhit daily records today.

In total, the country has 3,088,913 cases of the novel coronavirus, including 132,934 deaths, by far the most infections and fatalities of any country.

Today on a podcast produced by the Wall Street Journal, Anthony Fauci, MD, the director of the National Institute of Allergy and Infectious Diseases, said he thinks states seeing a spike in cases should consider shutting down local economies.

"Be mindful of what happens when you open up and throw caution to the wind," Fauci said.

In Tulsa, health officials said the increase in cases is likely at least partially tied to a Jun 20 campaign rally for President Trump and accompanying protests. The rally was held indoors with no enforced social distancing or mask use.

"In the past few days, we've seen almost 500 new cases, and we had several large events just over two weeks ago, so I guess we just connect the dots," Tulsa City-County Health Department Director Bruce Dart, MD, said yesterday.

Houston has seen an increase in the number of people dying at home, ProPublica reports, which could be an indicator that these deaths are caused by untested COVD-19 infections.

The uptick in the number of people dying before they can even reach a hospital in Houston parallels what happened in New York City in March and April.

Data collected by ProPublica from the Houston Fire Department show a 45% jump since February in the number of cardiac arrest calls that ended with paramedics declaring people dead upon arrival. In June, dead-on-arrival calls grew to nearly 300, more than 75 in excess of either of the previous two Junes.

Yesterday Texas reported 9,979 new cases of COVID-19, and said a record number of people were hospitalized: 9,610. Harris County, which includes most of Houston, has 39,311 cases and 407 deaths.

The Centers for Disease and Prevention (CDC) will revise its guidance on reopening of schools, according to Vice President Mike Pence. Pence made the comments yesterday during a news conferences at the US Department of Education.

"The president said today we just don't want the guidance to be too tough," Pence said. "That's the reason why, next week, CDC is going to be issuing a new set of tools, five different documents that will be giving even more clarity on the guidance going forward."

Public health officials, however, are concerned that the president's tweeted threats to withhold federal aid to schools that do not reopen are behind the CDC's new effort to update guidelines.

"The CDC has been saying that schools must open cautiously and follow science-based guidelines such as physical distancing, physical barriers and cleaning to help thwart COVID-19," American Public Health Association (APHA) Executive Director Georges C. Benjamin, MD, said in an APHA news release. "The Trump administration has no justification for overruling science-backed information that the CDC has initiated in school opening plans."

Today on "Good Morning America," CDC Director Robert Redfield, MD, clarified the agency's position on reopening guidelines.

"Our guidelines are our guidelines, but we are going to provide additional reference documents to aid basically communities that are trying to open K-through-12s," Redfield said. "It's not a revision of the guidelines; it's just to provide additional information to help schools be able to use the guidance we put forward."

In other US pandemic news:

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US notes 62000 COVID cases in another record-breaking day - CIDRAP

Mendocino County Health Officer Confirms 19 New COVID-19 Cases and First Outbreak at a Skilled Nursing Facility – Redheaded Blackbelt

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Press release from the County of Mendocino:

Today, Mendocino County Health Officer Dr. Noemi Doohan confirmed 19 new cases of COVID-19 reported to the County over the last 2 days. County staff has been working all weekend conducting case investigation and contact tracing. The number of Mendocino County COVID-19 cases is now 132 (91 Recovered; 1 hospitalized; 40 on home isolation).

Region

Number in Isolation

6

0

2

24

8

40

Mendocino County is experiencing a rise in COVID-19 cases and its important every resident help slow the spread of COVID-19 and keep our community safe by wearing a facial covering that covering the nose and mouth; practicing social distancing; avoiding gatherings, confined spaces and close contact with others. COVID-19 incubation period is up to 14 days and Public Health is concerned we may experience an additional spike in cases resulting from increased activity county-wide over the 4thof July holiday weekend.

Of the 19 new cases, 3 are residents at Sherwood Oaks Skilled Nursing Facility in Fort Bragg. On July 7 an employee of the facility tested positive for COVID-19 and was promptly placed into isolation. Following the positive case an immediate plan was made in collaboration with Public Health to test all the employees and residents. The results of these tests included 3 positive test for COVID-19, all of whom were residents of the facility. These results were reported to Public Health on July 11. Once the COVID-19 status of the employee was reported to the Skilled Nursing Facility (SNF) on July 7, the facility went immediately into outbreak response with full Personal Protective Equipment (PPE) for all staff and isolation of residents in their rooms. In addition, the facility was following theHealth Officers Medical Masking Orderwhich provides additional protections to SNFs.

The 3 new cases in the SNF were identified through testing conducted by the SNF on July 8 and processed at the Public Health Viral and Rickettsial Disease Lab (VRDL) in Richmond. The VRDL is available to the County for COVID-19 outbreak testing. All 3 individuals are currently asymptomatic. Case investigation and contract tracing was immediately initiated. The recent death at the facility tested negative for COVID-19 and the cause of death at this time is presumed to be unrelated to COVID-19. Public Health is doing further investigation and awaiting the death certificate. In addition, Public Health has reported this outbreak to the State as required and will be working with the State in support and review of the actions to contain the outbreak. Thus far Mendocino County is not on the State watch list. Additional testing will be conducted Monday, July 13, in effort to monitor and continue timely response to this outbreak.

Public Health and the SNFs throughout the County have been meeting weekly for months, led by our Medical Health Operational Area Coordinator (MHOAC), to allow a coordinated response to potential outbreaks and to ensure SNFs have sufficient PPE and prevention protection protocols in place. The County and SNFs follow all the State guidelines including; using Optum Serve to do surveillance testing for 100% of SNF staff monthly and offering SNF surveillance testing to residents through Public Health. The preparation, planning, frequently testing and adherence to State guidelines were a key factor in the quick and coordinated response to this outbreak.

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Mendocino County Health Officer Confirms 19 New COVID-19 Cases and First Outbreak at a Skilled Nursing Facility - Redheaded Blackbelt

Scientists scoff at Indian agency’s plan to have COVID-19 vaccine ready for use next month – Science Magazine

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A scientist at work at the Serum Institute of India, which is working on COVID-19 vaccines. Two Indian companies have received the green light to start human trials of their candidate vaccines.

By Sanjay KumarJul. 6, 2020 , 4:55 PM

Science's COVID-19 reporting is supported by the Pulitzer Center.

NEW DELHIThe apparent speed at which an Indian government agency aims to test and approve a homegrown COVID-19 vaccine has created an uproar among scientists both in India, which is increasingly overwhelmed by the new coronavirus, and abroad. A letter leaked on Twitter on Friday suggests the first vaccines could be rolled out by 15 August, which would leave far too little time for proper testing, critics say. The Indian Academy of Sciences calls the timeline unreasonable and without precedent.

Six Indian companies are developing vaccines against COVID-19. Last week, the Indian government gave two of them, Bharat Biotech and Zydus Cadila, permission to start phase I and II human clinical trials of their most advanced vaccines, named covaxin and ZyCov-D respectively.

For covaxin, Bharat Biotech has joined with the National Institute of Virology, which is part of the Indian Council of Medical Research (ICMR). (The company is separately developing COVID-19 vaccine candidates in collaboration with Thomas Jefferson University in Philadelphia and the University of Wisconsin, Madison.)

ICMR Director-General Balram Bhargava revealed the extremely tight deadline in a letter to hospitals designated to be involved in the Covaxin studies. It is envisaged to launch the vaccine for public health use latest by 15 August 2020 after completion of all clinical trials, Bhargava wrote. He asked the hospitals to fast-track all approvals for the vaccine and be ready to enroll participants no later than 7 July 2020, adding that noncompliance will be viewed very seriously.

But its absurd to think studies could show a vaccine to be safe and effective in less than 2 months, many scientists say. In my knowledge, such an accelerated development pathway has never ever been done for any kind of vaccine, says Anant Bhan, an independent ethics and policy researcher and past president of the International Association of Bioethics. This seems really, really rushed. The timeline carries potential risks and provides inadequate attention to required safety procedures, Bhan adds.

Clinical trials cannot be rushed, concurs Indian virologist and veteran vaccine researcher Thekkekara Jacob John, formerly of the Christian Medical College in Vellore. Even when expedited, phase I and phase II trials will take a minimum of 5 months, he says. The duration of a phase III trial would depend on several factors, including the number of subjects enrolled and decisions by a data safety monitoring board, but would probably add at least another 6 months, Jacob John says. ICMRs intentions may be good but the processes have been vitiated and the risk is it can derail the vaccine, he says.

Critics believe the target date is political: 15 August is Indias Independence Day, when Prime Minister Narendra Modi traditionally climbs the ramparts of the Red Fort in Delhi to give a long speech touting his governments achievements and make major announcements.

In a statement on Saturday, ICMR said Bhargava's letter was meant to cut unnecessary red tape, without bypassing any necessary process, and speed up recruitment of participants.

Faced with the unprecedented nature of the COVID-19 pandemic, and the consequent dislocation of the normal life, all other vaccine candidates across the globe have been similarly fast-tracked, the agency claimed. In reality, no other country has announced plans to roll out a vaccine this fast, and ICMR did not explain how it thinks it can accelerate the process. Bharat Biotech declined Sciences request for comment.

India is eagerly awaiting a COVID-19 vaccine. It just surpassed Russia as the country with the third-highest number of cases, after the United States and Brazil. There were 24,000 confirmed new cases on Sunday; the national tally stands at 697,413 cases and 19,693 deaths.

But India should keep in mind that most vaccine candidates fail, says Seth Berkley, CEO of Gavi, the Vaccine Alliance. Normally, the probability of success for a vaccine in the preclinical phase is around 7%, rising to 15% to 20% for vaccines that reach clinical tests, such as Covaxin and ZyCov-D, Berkley says.

ICMRs actions lower the credibility of Indian science, says T. Sundararaman, global coordinator of the Peoples Health Movement, a network of grassroots health activists, civil society organizations, and academic institutions. Its not about getting there first but to be able to do it well and it is good that India has been able to come up with candidate vaccines, which is not a small achievement.

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Scientists scoff at Indian agency's plan to have COVID-19 vaccine ready for use next month - Science Magazine

It’s been four months since the first COVID-19 case in Knox County – WBIR.com

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In over 120 days, lives have done a 180 in Knox County. Looking back over the last four months reveals what the community has experienced in that time.

KNOX COUNTY, Tenn. It's been exactly four months since the first COVID-19 diagnosis in Knox County.

The CDC marked Knoxville and Knox County as hot spots after positive cases nearly tripled in the last month.

As hospitalizations continue to rise, it's important to take a look back at where everything started.

Four months ago on a calendar seems like just yesterday, but four months living in a pandemic feels like a lifetime. March 12, 2020, is the day Knox County reported its first positive case of COVID-19.

At that point, Dr. Martha Buchanan, the director of the Knox County Health Department, said there was no community spread.

In over 120 days since then, life has done a 180. Cases have nearly tripled in the last month, and the Knox County Health Department reports 10 people have died from the virus.

But, how did we get here? Let's take a look back.

Not long after the virus started to spread in the community, Knox County officials implemented a "safer at home" order, closing nonessential businesses and asking families to stay inside and only go out for essentials.

"We understand the significant and in some cases devastating impact this will have on local businesses," Buchanan said, announcing the order in March.

The terms "flatten the curve" and "new normal" became household sayings. Families sacrificed parts of their lives to slow the spread. Churches found a new way to worship.

Volunteers made masks for the public, healthcare workers were celebrated. Education took on a new form, and employees worked from home.

The state reported nearly 700,000 unemployment claims were filed since March 15.

Slowly, businesses started to reopen.

"For the good of our state, social distancing must continue, but our economic shutdown cannot," Governor Bill Lee said in April.

The lingering health crisis is still here and cases aren't going away. Now, masks are required for indoor public spaces in Knox County and survivors are stressing the importance of taking it seriously.

Take precautions now, so the next four months' COVID-19 cases go down and the quality of life goes up.

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It's been four months since the first COVID-19 case in Knox County - WBIR.com

Top 12 Ways Artificial Intelligence Will Impact Healthcare

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April 30, 2018 -The healthcare industry is ripe for some major changes. From chronic diseases and cancer to radiology and risk assessment, there are nearly endless opportunities to leverage technology to deploy more precise, efficient, and impactful interventions at exactly the right moment in a patients care.

As payment structures evolve, patients demand more from their providers, and the volume of available data continues to increase at a staggering rate, artificial intelligence is poised to be the engine that drives improvements across the care continuum.

AI offers a number of advantages over traditional analytics and clinical decision-making techniques. Learning algorithms can become more precise and accurate as they interact with training data, allowing humans to gain unprecedented insights into diagnostics, care processes, treatment variability, and patient outcomes.

At the 2018 World Medical Innovation Forum (WMIF) on artificial intelligence presented by Partners Healthcare, a leading researchers and clinical faculty members showcased the twelve technologies and areas of the healthcare industry that are most likely to see a major impact from artificial intelligence within the next decade.

Every member of this Disruptive Dozen has the potential to produce a significant benefit to patients while possessing the potential for broad commercial success, said WMIF co-chairs Anne Kiblanksi, MD, Chief Academic Officer at Partners Healthcare and Gregg Meyer, MD, Chief Clinical Officer.

With the help of experts from across the Partners Healthcare system, including faculty from Harvard Medical School (HMS), moderators Keith Dreyer, DO, PhD, Chief Data Science Officer at Partners and Katherine Andriole, PhD, Director of Research Strategy and Operations at Massachusetts General Hospital (MGH), counted down the top 12 ways artificial intelligence will revolutionize the delivery and science of healthcare.

Using computers to communicate is not a new idea by any means, but creating direct interfaces between technology and the human mind without the need for keyboards, mice, and monitors is a cutting-edge area of research that has significant applications for some patients.

Neurological diseases and trauma to the nervous system can take away some patients abilities to speak, move, and interact meaningfully with people and their environments. Brain-computer interfaces (BCIs) backed by artificial intelligence could restore those fundamental experiences to those who feared them lost forever.

If Im in the neurology ICU on a Monday, and I see someone who has suddenly lost the ability to move or to speak, we want to restore that ability to communicate by Tuesday, said Leigh Hochberg, MD, PhD, Director of the Center for Neurotechnology and Neurorecovery at MGH.

By using a BCI and artificial intelligence, we can decode the neural activates associated with the intended movement of ones hand, and we should be able to allow that person to communicate the same way as many people in this room have communicated at least five times over the course of the morning using a ubiquitous communication technology like a tablet computer or phone.

Brain-computer interfaces could drastically improve quality of life for patients with ALS, strokes, or locked-in syndrome, as well as the 500,000 people worldwide who experience spinal cord injuries every year.

Radiological images obtained by MRI machines, CT scanners, and x-rays offer non-invasive visibility into the inner workings of the human body. But many diagnostic processes still rely on physical tissue samples obtained through biopsies, which carry risks including the potential for infection.

Artificial intelligence will enable the next generation of radiology tools that are accurate and detailed enough to replace the need for tissue samples in some cases, experts predict.

We want to bring together the diagnostic imaging team with the surgeon or interventional radiologist and the pathologist, said Alexandra Golby, MD, Director of Image-Guided Neurosurgery at Brigham & Womens Hospital (BWH). That coming together of different teams and aligning goals is a big challenge.

If we want the imaging to give us information that we presently get from tissue samples, then were going to have to be able to achieve very close registration so that the ground truth for any given pixel is known.

Succeeding in this quest may allow clinicians to develop a more accurate understanding of how tumors behave as a whole instead of basing treatment decisions on the properties of a small segment of the malignancy.

Providers may also be able to better define the aggressiveness of cancers and target treatments more appropriately.

Artificial intelligence is helping to enable virtual biopsies and advance the innovative field of radiomics, which focuses on harnessing image-based algorithms to characterize the phenotypes and genetic properties of tumors.

Shortages of trained healthcare providers, including ultrasound technicians and radiologists can significantly limit access to life-saving care in developing nations around the world.

More radiologists work in the half-dozen hospitals lining the renowned Longwood Avenue in Boston than in all of West Africa, the session pointed out.

Artificial intelligence could help mitigate the impacts of this severe deficit of qualified clinical staff by taking over some of the diagnostic duties typically allocated to humans.

For example, AI imaging tools can screen chest x-rays for signs of tuberculosis, often achieving a level of accuracy comparable to humans. This capability could be deployed through an app available to providers in low-resource areas, reducing the need for a trained diagnostic radiologist on site.

The potential for this tech to increase access to healthcare is tremendous, said Jayashree Kalpathy-Cramer, PhD, Assistant in Neuroscience at MGH and Associate Professor of Radiology at HMS.

Source: World Medical Innovation Forum 2018

However, algorithm developers must be careful to account for the fact that disparate ethnic groups or residents of different regions may have unique physiologies and environmental factors that will influence the presentation of disease.

The course of a disease and population affected by the disease may look very different in India than in the US, for example, she said.

As were developing these algorithms, its very important to make sure that the data represents a diversity of disease presentations and populations we cant just develop an algorithm based on a single population and expect it to work as well on others.

EHRs have played an instrumental role in the healthcare industrys journey towards digitalization, but the switch has brought myriad problems associated with cognitive overload, endless documentation, and user burnout.

EHR developers are now using artificial intelligenceto create more intuitive interfaces and automate some of the routine processes that consume so much of a users time.

Users spend the majority of their time on three tasks: clinical documentation, order entry, and sorting through the in-basket, said Adam Landman, MD, Vice President and CIO at Brigham Health.

Voice recognition and dictation are helping to improve the clinical documentation process, butnatural language processing(NLP) tools might not be going far enough.

I think we may need to be even bolder and consider changes like video recording a clinical encounter, almost like police wear body cams, said Landman. And then you can use AI and machine learning to index those videos for future information retrieval.

And just like in the home, where were using Siri and Alexa, the future will bring virtual assistants to the bedside for clinicians to use with embedded intelligence for order entry.

Artificial intelligence may also help to process routine requests from the inbox, like medication refills and result notifications. It may also help to prioritize tasks that truly require the clinicians attention, Landman added, making it easier for users to work through their to-do lists.

Antibiotic resistance is a growing threat to populations around the world as overuse of these critical drugs fosters the evolution of superbugs that no longer respond to treatments. Multi-drug resistant organisms can wreak havoc in the hospital setting, and claim thousands of lives every year.

C. difficilealone accounts for approximately $5 billion in annual costs for the US healthcare system and claims more than 30,000 lives.

Electronic health record data can help toidentify infection patternsand highlight patients at risk before they begin to show symptoms. Leveraging machine learning and AI tools to drive these analytics can enhance their accuracy and create faster, more accurate alerts for healthcare providers.

AI tools can live up to the expectation for infection control and antibiotic resistance, Erica Shenoy, MD, PhD, Associate Chief of the Infection Control Unit at MGH.

If they dont, then thats really a failure on all of our parts. For the hospitals sitting on mountains of EHR data and not using them to the fullest potential, to industry thats not creating smarter, faster clinical trial design, and for EHRs that are creating these data not to use themthat would be a failure.

Pathologists provide one of the most significant sources of diagnostic data for providers across the spectrum of care delivery, says Jeffrey Golden, MD, Chair of the Department of Pathology at BWH and a professor of pathology at HMS.

Seventy percent of all decisions in healthcare are based on a pathology result, he said. Somewhere between 70 and 75 percent of all the data in an EHR are from a pathology result. So the more accurate we get, and the sooner we get to the right diagnosis, the better were going to be. Thats what digital pathology and AI has the opportunity to deliver.

Analytics that can drill downto the pixel levelon extremely large digital images can allow providers to identify nuances that may escape the human eye.

Were now getting to the point where we can do a better job of assessing whether a cancer is going to progress rapidly or slowly and how that might change how patients will be treated based on an algorithm rather than clinical staging or the histopathologic grade, said Golden. Thats going to be a huge advance.

Artificial intelligence can also improve productivity byidentifying features of interestin slides before a human clinician reviews the data, he added.

AI can screen through slides and direct us to the right thing to look at so we can assess whats important and whats not. That increases the efficiency of the use of the pathologist and increases the value of the time they spend for each case.

Smart devices are taking over the consumer environment, offering everything from real-time video from the inside of a refrigerator to cars that can detect when the driver is distracted.

In the medical environment,smart devicesare critical for monitoring patients in the ICU and elsewhere. Using artificial intelligence to enhance the ability to identify deterioration, suggest thatsepsisis taking hold, or sense the development of complications can significantly improve outcomes and may reduce costs related to hospital-acquired condition penalties.

Source: Thinkstock

When were talking about integrating disparate data from across the healthcare system, integrating it, and generating an alert that would alert an ICU doctor to intervene early on the aggregation of that data is not something that a human can do very well, said Mark Michalski, MD, Executive Director of the MGH & BWH Center for Clinical Data Science.

Inserting intelligent algorithms into these devices can reduce cognitive burdens for physicians while ensuring that patients receive care in as timely a manner as possible.

Immunotherapy is one of the most promising avenues for treating cancer. By using the bodys own immune system to attack malignancies, patients may be able to beat stubborn tumors. However, only a small number of patients respond to current immunotherapy options, and oncologists still do not have a precise and reliable method for identifying which patients will benefit from this option.

Machine learning algorithms and their ability to synthesize highly complex datasets may be able to illuminate new options for targeting therapies to an individuals unique genetic makeup.

Recently, the most exciting development has been checkpoint inhibitors, which block some of the proteins made by some times of immune cells, explained Long Le, MD, PhD, Director of Computational Pathology and Technology Development at the MGH Center for Integrated Diagnostics. But we still dont understand all of the disease biology. This is a very complex problem.

We definitely need more patient data. The therapies are relatively new, so not a lot of patients have actually been put on these drugs. So whether we need to integrate data within one institution or across multiple institutions is going to be a key factor in terms of augmenting the patient population to drive the modeling process.

EHRs are a goldmine of patient data, but extracting and analyzing that wealth of information in an accurate, timely, and reliable manner has been a continual challenge for providers and developers.

Data quality and integrity issues, plus a mishmash of data formats, structured and unstructured inputs, and incomplete records have made it very difficult to understand exactly how to engage in meaningful risk stratification, predictive analytics, and clinical decision support.

Part of the hard work is integrating the data into one place, observed Ziad Obermeyer, MD, Assistant Professor of Emergency Medicine at BWH and Assistant Professor at HMS. But another problem is understanding what it is youre getting when youre predicting a disease in an EHR.

You might hear that an algorithm can predict depression or stroke, but when you scratch the surface, you find what theyre actually predicting is a billing code for stroke. Thats very different from stroke itself.

Relying on MRI results might appear to offer a more concrete dataset, he continued.

But now you have to think about who can afford the MRI, and who cant? So what you end up predicting isnt what you thought you were predicting. You might be predicting billing for a stroke in people who can pay for a diagnostic rather than some sort of cerebral ischemia.

EHR analytics have produced many successful risk scoring and stratification tools, especially when researchers employ deep learning techniques to identify novel connections between seemingly unrelated datasets.

But ensuring that those algorithms do not confirm hidden biases in the data is crucial for deploying tools that will truly improve clinical care, Obermeyer maintained.

The biggest challenge will be making sure exactly what were predicting even before we start opening up the black box and looking at how were predicting it, he said.

Almost all consumers now have access to devices with sensors that can collect valuable data about their health. From smartphones with step trackers to wearables that can track a heartbeat around the clock, a growing proportion of health-related data is generated on the go.

Collecting and analyzing this data and supplementing it with patient-provided information through apps and other home monitoring devices can offer a unique perspective into individual and population health.

Artificial intelligence will play a significant role in extracting actionable insights from this large and varied treasure trove of data.

But helping patients get comfortable with sharing data from this intimate, continual monitoring may require a little extra work, says Omar Arnaout, MD, Co-director of the Computation Neuroscience Outcomes Center and an attending neurosurgeon at BWH.

As a society, weve been pretty liberal with our digital data, he said. But as things come into our collective consciousness like Cambridge Analytica and Facebook, people will become more and more prudent about who they share what kinds of data with.

However, patients tend to trust their physicians more than they might trust a big company like Facebook, he added, which may help to ease any discomfort with contributing data to large-scale research initiatives.

Theres a very good chance [wearable data will have a major impact] because our care is very episodic and the data we collect is very coarse, said Arnaout. By collecting granular data in a continuous fashion, theres a greater likelihood that the data will help us take better care of patients.

Continuing the theme of harnessing the power of portable devices, experts believe that images taken from smartphones and other consumer-grade sources will be an important supplement to clinical quality imaging especially in underserved populations or developing nations.

The quality of cell phone cameras is increasing every year, and can produce images that are viable for analysis by artificial intelligence algorithms. Dermatology and ophthalmology are early beneficiaries of this trend.

Researchers in the United Kingdom have even developed a tool that identifies developmental diseases by analyzing images of a childs face. The algorithm can detect discrete features, such as a childs jaw line, eye and nose placement, and other attributes that might indicate a craniofacial abnormality. Currently, the tool can match the ordinary images to more than 90 disorders to provide clinical decision support.

The majority of the population is equipped with pocket-sized, powerful devices that have a lot of different sensors built in, said Hadi Shafiee, PhD, Director of the Laboratory of Micro/Nanomedicine and Digital Health at BWH.

This is a great opportunity for us. Almost every major player in the industry has started to build AI software and hardware into their devices. Thats not a coincidence. Every day in our digital world, we generate more than 2.5 million terabytes of data. In cell phones, the manufacturers believe they can use that data with AI to provide much more personalized and faster and smarter services.

Source: Thinkstock

Using smartphones to collect images of eyes, skin lesions, wounds, infections, medications, or other subjects may be able to help underserved areas cope with a shortage of specialists while reducing the time-to-diagnosis for certain complaints.

There is something big happening, said Shafiee. We can leverage that opportunity to address some of the important problems with have in disease management at the point of care.

As the healthcare industry shifts away from fee-for-service, so too is it moving further and further from reactive care. Getting ahead of chronic diseases, costly acute events, and sudden deterioration is the goal of every provider and reimbursement structures are finally allowing them to develop the processes that will enable proactive, predictive interventions.

Artificial intelligence will provide much of the bedrock for that evolution by powering predictive analytics and clinical decision support tools that clue providers in to problems long before they might otherwise recognize the need to act.

AI can provide earlier warnings for conditions like seizures or sepsis, which often require intensive analysis of highly complex datasets.

Machine learning can also help support decisions around whether or not to continue care for critically ill patients, such as those who have entered a coma after cardiac arrest, says Brandon Westover, MD, PhD, Director of the MGH Clinical Data Animation Center.

Typically, providers must visually inspect EEG data from these patients, he explained. The process is time-consuming and subjective, and the results may vary with the skill and experience of the individual clinician.

In these patients, trends might be slowly evolving, he said. Sometimes when were looking to see if someone is recovering, we take the data from ten seconds of monitoring at a time. But trying to see if it changed from ten seconds of data taken 24 hours ago is like trying to look if your hair is growing longer.

But if you have an AI algorithm and lots and lots of data from many patients, its easier to match up what youre seeing to long term patterns and maybe detect subtle improvements that would impact your decisions around care.

Leveraging AI for clinical decision support, risk scoring, and early alerting is one of the most promising areas of development for this revolutionary approach to data analysis.

By powering a new generation of tools and systems that make clinicians more aware of nuances, more efficient when delivering care, and more likely to get ahead of developing problems, AI will usher in a new era of clinical quality and exciting breakthroughs in patient care.

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Top 12 Ways Artificial Intelligence Will Impact Healthcare

Using Artificial Intelligence to Address Criminal Justice …

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Intelligent machines have long been the subject of science fiction. However, we now live in an era in which artificial intelligence (Al) is a reality, and it is having very real and deep impacts on our daily lives. From phones to cars to finances and medical care, AI is shifting the way we live.

AI applications can be found in many aspects of our lives, from agriculture to industry, communications, education, finance, government, service, manufacturing, medicine, and transportation. Even public safety and criminal justice are benefiting from AI. For example, traffic safety systems identify violations and enforce the rules of the road, and crime forecasts allow for more efficient allocation of policing resources. AI is also helping to identify the potential for an individual under criminal justice supervision to reoffend.[1]

Research supported by NIJ is helping to lead the way in applying AI to address criminal justice needs, such as identifying individuals and their actions in videos relating to criminal activity or public safety, DNA analysis, gunshot detection, and crime forecasting.

AI is a rapidly advancing field of computer science. In the mid-1950s, John McCarthy, who has been credited as the father of AI, defined it as the science and engineering of making intelligent machines.[2] Conceptually, AI is the ability of a machine to perceive and respond to its environment independently and perform tasks that would typically require human intelligence and decision-making processes, but without direct human intervention.

See A Brief History of Artificial Intelligence

One facet of human intelligence is the ability to learn from experience. Machine learning is an application of AI that mimics this ability and enables machines and their software to learn from experience.[3] Particularly important from the criminal justice perspective is pattern recognition. Humans are efficient at recognizing patterns and, through experience, we learn to differentiate objects, people, complex human emotions, information, and conditions on a daily basis. AI seeks to replicate this human capability in software algorithms and computer hardware. For example, self-learning algorithms use data sets to understand how to identify people based on their images, complete intricate computational and robotics tasks, understand purchasing habits and patterns online, detect medical conditions from complex radiological scans, and make stock market predictions.

AI is being researched as a public safety resource in numerous ways. One particular AI application facial recognition can be found everywhere in both the public and the private sectors.[4] Intelligence analysts, for example, often rely on facial images to help establish an individuals identity and whereabouts. Examining the huge volume of possibly relevant images and videos in an accurate and timely manner is a time-consuming, painstaking task, with the potential for human error due to fatigue and other factors. Unlike humans, machines do not tire. Through initiatives such as the Intelligence Advanced Research Projects Activitys Janus computer-vision project, analysts are performing trials on the use of algorithms that can learn how to distinguish one person from another using facial features in the same manner as a human analyst.[5]

See

The U.S. Department of Transportation is also looking to increase public safety through researching, developing, and testing automatic traffic accident detection based on video to help maintain safe and efficient commuter traffic over various locations and weather, lighting, and traffic conditions.[6] AI algorithms are being used in medicine to interpret radiological images, which could have important implications for the criminal justice and medical examiner communities when establishing cause and manner of death.[7] AI algorithms have also been explored in various disciplines in forensic science, including DNA analysis.[8]

AI is also quickly becoming an important technology in fraud detection.[9] Internet companies like PayPal stay ahead of fraud attempts by using volumes of data to continuously train their fraud detection algorithms to predict and recognize anomalous patterns and to learn to recognize new patterns.[10]

The AI research that NIJ supports falls primarily into four areas: public safety video and image analysis, DNA analysis, gunshot detection, and crime forecasting.

Video and image analysis is used in the criminal justice and law enforcement communities to obtain information regarding people, objects, and actions to support criminal investigations. However, the analysis of video and image information is very labor-intensive, requiring a significant investment in personnel with subject matter expertise. Video and image analysis is also prone to human error due to the sheer volume of information, the fast pace of changing technologies such as smartphones and operating systems, and a limited number of specialized personnel with the knowledge to process such information.

AI technologies provide the capacity to overcome such human errors and to function as experts. Traditional software algorithms that assist humans are limited to predetermined features such as eye shape, eye color, and distance between eyes for facial recognition or demographics information for pattern analysis. AI video and image algorithms not only learn complex tasks but also develop and determine their own independent complex facial recognition features/parameters to accomplish these tasks, beyond what humans may consider. These algorithms have the potential to match faces, identify weapons and other objects, and detect complex events such as accidents and crimes in progress or after the fact.

In response to the needs of the criminal justice and law enforcement communities, NIJ has invested in several areas to improve the speed, quality, and specificity of data collection, imaging, and analysis and to improve contextual information.

For instance, to understand the potential benefits of AI in terms of speed, researchers at the University of Texas at Dallas, with funding from NIJ and in partnership with the FBI and the National Institute of Standards and Technology, are assessing facial identification by humans and examining methods for effectively comparing AI algorithms and expert facial examiners. Preliminary results show that when the researchers limit the recognition time to 30 seconds, AI-based facial-recognition algorithms developed in 2017 perform comparably to human facial examiners.[11] The implications of these findings are that AI-based algorithms can potentially be used as a second pair of eyes to increase the accuracy of expert human facial examiners and to triage data to increase productivity.

In addition, in response to the need for higher quality information and the ability to use lower quality images more effectively, Carnegie Mellon University is using NIJ funding to develop AI algorithms to improve detection, recognition, and identification. One particularly important aspect is the universitys work on images in which an individuals face is captured at different angles or is partially to the side, and when the individual is looking away from the camera, obscured by masks or helmets, or blocked by lamp posts or lighting. The researchers are also working with low-quality facial image construction, including images with poor resolution and low ambient light levels, where the image quality makes facial matching difficult. NIJs test and evaluation center is currently testing and evaluating these algorithms.[12]

Finally, to decipher a license plate (which could help identify a suspect or aid in an investigation) or identify a person in extremely low-quality images or video, researchers at Dartmouth College are using AI algorithms that systematically degrade high-quality images and compare them with low-quality ones to better recognize lower quality images and video. For example, clear images of numbers and letters are slowly degraded to emulate low-quality images. The degraded images are then expressed and catalogued as mathematical representations. These degraded mathematical representations can then be compared with low-quality license plate images to help identify the license plate.[13]

Also being explored is the notion of scene understanding, or the ability to develop text that describes the relationship between objects (people, places, and things) in a series of images to provide context. For example, the text may be Pistol being drawn by a person and discharging into a store window. The goal is to detect objects and activities that will help identify crimes in progress for live observation and intervention as well as to support investigations after the fact.[14] Scene understanding over multiple scenes can indicate potentially important events that law enforcement should view to confirm and follow. One group of researchers at the University of Central Florida, in partnership with the Orlando Police Department, is using NIJ funding to develop algorithms to identify objects in videos, such as people, cars, weapons, and buildings, without human intervention. They are also developing algorithms to identify actions such as traffic accidents and violent crimes.

Another important aspect of AI is the ability to predict behavior. In contrast to the imaging and identification of criminal activity in progress, the University of Houston has used NIJ funding to develop algorithms that provide continuous monitoring to assess activity and predict emergent suspicious and criminal behavior across a network of cameras. This work also concentrates on using clothing, skeletal structure, movement, and direction prediction to identify and re-acquire people of interest across multiple cameras and images.[15]

AI can also benefit the law enforcement community from a scientific and evidence processing standpoint. This is particularly true in forensic DNA testing, which has had an unprecedented impact on the criminal justice system over the past several decades.

Biological material, such as blood, saliva, semen, and skin cells, can be transferred through contact with people and objects during the commission of a crime. As DNA technology has advanced, so has the sensitivity of DNA analysis, allowing forensic scientists to detect and process low-level, degraded, or otherwise unviable DNA evidence that could not have been used previously. For example, decades-old DNA evidence from violent crimes such as sexual assaults and homicide cold cases is now being submitted to laboratories for analysis. As a result of increased sensitivity, smaller amounts of DNA can be detected, which leads to the possibility of detecting DNA from multiple contributors, even at very low levels. These and other developments are presenting new challenges for crime laboratories. For instance, when using highly sensitive methods on items of evidence, it may be possible to detect DNA from multiple perpetrators or from someone not associated with the crime at all thus creating the issue of DNA mixture interpretation and the need to separate and identify (or deconvolute) individual profiles to generate critical investigative leads for law enforcement.

AI may have the potential to address this challenge. DNA analysis produces large amounts of complex data in electronic format; these data contain patterns, some of which may be beyond the range of human analysis but may prove useful as systems increase in sensitivity. To explore this area, researchers at Syracuse University partnered with the Onondaga County Center for Forensic Sciences and the New York City Office of Chief Medical Examiners Department of Forensic Biology to investigate a novel machine learning-based method of mixture deconvolution. With an NIJ research award, the Syracuse University team worked to combine the strengths of approaches involving human analysts with data mining and AI algorithms. The team used this hybrid approach to separate and identify individual DNA profiles to minimize the potential weaknesses inherent in using one approach in isolation. Although ongoing evaluation of the use of AI techniques is needed and there are many factors that can influence the ability to parse out individual DNA donors, research shows that AI technology has the potential to assist in these complicated analyses.[16]

The discovery of pattern signatures in gunshot analysis offers another area in which to use AI algorithms. In one project, NIJ funded Cadre Research Labs, LLC, to analyze gunshot audio files from smartphones and smart devices based on the observation that the content and quality of gunshot recordings are influenced by firearm and ammunition type, the scene geometry, and the recording device used.[17] Using a well-defined mathematical model, the Cadre scientists are working to develop algorithms to detect gunshots, differentiate muzzle blasts from shock waves, determine shot-to-shot timings, determine the number of firearms present, assign specific shots to firearms, and estimate probabilities of class and caliber all of which could help law enforcement in investigations.[18]

Predictive analysis is a complex process that uses large volumes of data to forecast and formulate potential outcomes. In criminal justice, this job rests mainly with police, probation practitioners, and other professionals, who must gain expertise over many years. The work is time-consuming and subject to bias and error.[19]

With AI, volumes of information on law and legal precedence, social information, and media can be used to suggest rulings, identify criminal enterprises, and predict and reveal people at risk from criminal enterprises. NIJ-supported researchers at the University of Pittsburgh are investigating and designing computational approaches to statutory interpretation that could potentially increase the speed and quality of statutory interpretation performed by judges, attorneys, prosecutors, administrative staff, and other professionals. The researchers hypothesize that a computer program can automatically recognize specific types of statements that play the most important roles in statutory interpretation. The goal is to develop a proof-of-concept expert system to support interpretation and perform it automatically for cybercrime.[20]

AI is also capable of analyzing large volumes of criminal justice-related records to predict potential criminal recidivism. Researchers at the Research Triangle Institute, in partnership with the Durham Police Department and the Anne Arundel Sheriffs Department, are working to create an automated warrant service triage tool for the North Carolina Statewide Warrant Repository. The NIJ-supported team is using algorithms to analyze data sets with more than 340,000 warrant records. The algorithms form decision trees and perform survival analysis to determine the time span until the next occurrence of an event of interest and predict the risk of re-offending for absconding offenders (if a warrant goes unserved). This model will help practitioners triage warrant service when backlogs exist. The resulting tool will also be geographically referenced so that practitioners can pursue concentrations of high-risk absconders along with others who have active warrants to optimize resources.[21]

AI can also help determine potential elder victims of physical and financial abuse. NIJ-funded researchers at the University of Texas Health Science Center at Houston used AI algorithms to analyze elder victimization. The algorithms can determine the victim, perpetrator, and environmental factors that distinguish between financial exploitation and other forms of elder abuse. They can also differentiate pure financial exploitation (when the victim of financial exploitation experiences no other abuse) from hybrid financial exploitation (when physical abuse or neglect accompanies financial exploitation). The researchers hope that these data algorithms can be transformed into web-based applications so that practitioners can reliably determine the likelihood that financial exploitation is occurring and quickly intervene.[22]

Finally, AI is being used to predict potential victims of violent crime based on associations and behavior. The Chicago Police Department and the Illinois Institute of Technology used algorithms to collect information and form initial groupings that focus on constructing social networks and performing analysis to determine potential high-risk individuals. This NIJ-supported research has since become a part of the Chicago Police Departments Violence Reduction Strategy.[23]

Every day holds the potential for new AI applications in criminal justice, paving the way for future possibilities to assist in the criminal justice system and ultimately improve public safety.

Video analytics for integrated facial recognition, the detection of individuals in multiple locations via closed-circuit television or across multiple cameras, and object and activity detection could prevent crimes through movement and pattern analysis, recognize crimes in progress, and help investigators identify suspects. With technology such as cameras, video, and social media generating massive volumes of data, AI could detect crimes that would otherwise go undetected and help ensure greater public safety by investigating potential criminal activity, thus increasing community confidence in law enforcement and the criminal justice system. AI also has the potential to assist the nations crime laboratories in areas such as complex DNA mixture analysis.

Pattern analysis of data could be used to disrupt, degrade, and prosecute crimes and criminal enterprises. Algorithms could also help prevent victims and potential offenders from falling into criminal pursuits and assist criminal justice professionals in safeguarding the public in ways never before imagined.

AI technology also has the potential to provide law enforcement with situational awareness and context, thus aiding in police well-being due to better informed responses to possibly dangerous situations. Technology that includes robotics and drones could also perform public safety surveillance, be integrated into overall public safety systems, and provide a safe alternative to putting police and the public in harms way. Robotics and drones could also perform recovery, provide valuable intelligence, and augment criminal justice professionals in ways not yet contrived.

By using AI and predictive policing analytics integrated with computer-aided response and live public safety video enterprises, law enforcement will be better able to respond to incidents, prevent threats, stage interventions, divert resources, and investigate and analyze criminal activity. AI has the potential to be a permanent part of our criminal justice ecosystem, providing investigative assistance and allowing criminal justice professionals to better maintain public safety.

On May 3, 2016, the White House announced a series of actions to spur public dialogue on artificial intelligence (AI), identify challenges and opportunities related to this technology, aid in the use of Al for more effective government, and prepare for the potential benefits and risks of Al. As part of these actions, the White House directed the creation of a national strategy for AI research and development. Following is a summary of the plans areas and intent.[24]

Manufacturing

Logistics

Finance

Transportation

Agriculture

Marketing

Communications

Science and Technology

Education

Medicine

Law

Personal Services

Security and Law Enforcement

Safety and Prediction

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This article was published as part of NIJ Journal issue number 280, December 2018.

This article discusses the following grants:

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Using Artificial Intelligence to Address Criminal Justice ...

Augmented Intelligence is the New Intelligence – Analytics Insight

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The future of decision-making includes an inventive blend of information, analytics, and artificial intelligence (AI), with the perfect scramble of human judgment. The outcome is augmented intelligence, where the analytical force and speed of AI assumes control over most of data processing, controlling human workers to make progressively agile, more intelligent choices and find new discoveries.

The development of analytics has caught the consideration of the heads of significant organizations. However, regardless of progressions throughout the years, few have had the option to stay aware of how to utilize analytics and AI among employees, in processes, and with appropriate oversight. The outcome is a lot of smart thoughts and technologies, however, applications that miss the mark regarding their potential.

Today, you can plug data into AI, and it can make its own models and make predictive recommendations. In any case, these models dont exist in a vacuum. They include data sources and outputs that impact the rest of your business. You need to consider how these models fit in and how to organize the insights from data. Also, you need governance over augmented intelligence to see that the automation is working and individuals know their job in the new man-meets-machine workforce.

If you are putting resources into analytics and AI, at that point think beyond data and technology. You need bilingual ability to bridge the gaps between industry and technology, and build up the correct solutions. You additionally need to consider the change in perspective in how man and machine will cooperate. At exactly that point would you be able to present a winning application and get the most value out of investments.

Augmented intelligence is an elective conceptualization of artificial intelligence that centers around AIs assistive job, accentuating the fact that cognitive technology is intended to improve human intelligence instead of supplanting it. The decision of the word augmented, which signifies to improve, strengthens the job human intelligence plays when utilizing AI and deep learning algorithms to find connections and take care of issues.

Platforms that offer Augmented Intelligence can accumulate a wide range of data (both structured and unstructured) from numerous sources, across different and siloed systems and they present that data such that gives human workers a total 360-degree perspective on every client.

The knowledge extricated from that data and introduced to the client is deeper and more noteworthy than ever before. Thus, workers are better educated on whats going on in their industry, what may influence their clients and the opportunities or threats that may emerge. Joining this abundance of data with the human touch is the thing that makes this innovation so incredible.

Some industry experts believe that the term artificial intelligence is excessively firmly connected to mainstream society and sci-fi, driving the overall population to have unreasonable feelings of trepidation about AI and unlikely assumptions regarding how autonomous robots and other smart frameworks will change the working environment and life in general.

Researchers and marketers trust the term augmented intelligence, which has an increasingly neutral connotation, will assist individuals in understanding that AI programming will just improve products and services, not supplant the people that use them.

Most companies have hills of information yet hardly any insights to advance positive business results. They struggle to accomplish ROI, for example, revenue growth, better customer experiences, and regulatory compliance, as well as to build an analytics capability for the future.

Augmented intelligence joins the strengths of people and machines when prospecting a value from data. To be specific, you can augment human instinct with smart algorithms that give quick, information driven predictive insights. These insights can assist individuals with overhauling functions, detect patterns, find strategic opportunities, and turn data into action.

Planned to extend human cognitive abilities, augmented intelligence is not quite the same as straight automation. Looking at the situation objectively, most procedures later on will be intended for straight-through processing, where there will be no people engaged with the procedure. As of now, that is beyond the realm of imagination on the grounds that in 25-30% of cases, you need people to step in.

Consider an airplane autopilot. In present day aviation, the autopilot can work freely, controlling heading and altitude, or it very well may be combined with a navigation system and fly pre-programmed, when the airplane has effectively gotten airborne. You despite everything need a pilot for departure and landing, for the time being. Ideally, an autopilot framework would consolidate human knowledge, in addition to experience focused through the prism of intuition. The outcome would be human judgment broadened by means of augmented intelligence.

To completely welcome the advantages and capability of augmented intelligence in analytics, it is important to totally re-engineer your mentality. You are not structuring a world that is predominantly manual with 30-40% automation. The objective is to make a completely new procedure, in a world that is predominantly automated and intended for 20% manual exemptions.

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Augmented Intelligence is the New Intelligence - Analytics Insight

MULTIMEDIA UPDATE – New Research Reveals Adoption and Implementation of Artificial Intelligence in the Enterprise – GlobeNewswire

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State of Artificial Intelligence 2020

300 technology decision makers were surveyed to uncover the ways companies are approaching and implementing emerging technologies like Artificial Intelligence (AI) to grow business and surpass the competition.

SAN FRANCISCO, July 09, 2020 (GLOBE NEWSWIRE) -- Informa Tech media brands, InformationWeek and ITPro Today, today announced findings from their latest research survey the 2020 State of Artificial Intelligence. The team surveyed technology decision makers across North American companies to uncover the ways organizations are approaching and implementing emerging technologies specifically artificial intelligence (AI) and the Internet of Things (IoT) in order to grow and get ahead of the competition.

Key Findings in the 2020 State of Artificial Intelligence

To download a complimentary copy of The 2020 State of Artificial Intelligence, click here.

Media interested in receiving a copy of the report or the State of AI infographic should contact Briana Pontremoli at Briana.Pontremoli@informa.com.

2020 State of Artificial Intelligence Report MethodologyThe survey collected opinions from nearly 300 business professionals at companies engaged with AI-related projects. Nearly 90% of respondents have an IT or technology-related job function, such as application development, security, Internet of Things, networking, cloud, or engineering. Just over half of respondents work in a management capacity, with titles such as C-level executive, director, manager, or vice president. One half are from large companies with 1,000 or more employees, and 20% work at companies with 100 to 999 employees.

About Informa TechInforma Tech is a market leading provider of integrated research, media, training and events to the global Technology community. We're an international business of more than 600 colleagues, operating in more than 20 markets. Our aim is to inspire the Technology community to design, build and run a better digital world through research, media, training and event brands that inform, educate and connect. Over 7,000 professionals subscribe to our research, with 225,000 delegates attending our events and over 18,000 students participating in our training programs each year, and nearly 4 million people visiting our digital communities each month. Learn more about Informa Tech.

Media Contact:Briana PontremoliInforma Tech PRbriana.pontremoli@informa.com

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/416bdfd6-7702-4850-94b0-4838cf3a396f

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MULTIMEDIA UPDATE - New Research Reveals Adoption and Implementation of Artificial Intelligence in the Enterprise - GlobeNewswire

Consumer Demand for Eco-friendly Products Set to Boost the Prospects of the Wireless Test System Market 2018 2026 – 3rd Watch News

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The global Wireless Test System market gives detailed Evaluation about all of the Important aspects related to the market. The study on international Wireless Test System economy, offers deep insights regarding the Wireless Test System market covering all of the crucial aspects of the marketplace. Moreover, the report provides historical information with prospective forecast over the forecast period. Various important factors like market trends, revenue growth patterns market stocks and supply and demand are contained in almost all the market research document for every business. A number of the important aspects analysed in the report contains market share, creation, key regions, revenue rate as well as key players.

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Consumer Demand for Eco-friendly Products Set to Boost the Prospects of the Wireless Test System Market 2018 2026 - 3rd Watch News

NKY Startup Community Awarded $510000 from State – The River City News

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Northern Kentucky Tri-ED and Blue North, the community for startups and small businesses in Northern Kentucky, announced an award of a $510,000 RISE grant for the new fiscal year from the Kentucky Cabinet for Economic Developments (KCED) Office of Entrepreneurship.

Tri-ED launched Blue North as the brand for its entrepreneurship program and services in 2019 after it received a grant last year from KCED to serve entrepreneurs in Northern Kentucky. With the support of Tri-ED, KCED, and the Northern Kentucky community, Blue North has been serving and connecting entrepreneurs, studying and mapping the regional ecosystem, and laying the groundwork for Blue North to become an independent organization.

At the beginning of July, Blue North began operating as an independent Limited Liability Company (LLC) - serving the Northern Kentucky community - under the leadership of Executive Director Brit Fitzpatrick and a regional board of directors. Fitzpatrick was hired as interim director of entrepreneurship by Lee Crume, president and CEO of Tri-ED, and named director in October 2019.

Throughout the last year, the Blue North team has solidified our four focus areas for our eight-county region and developed evidence-based strategies to serve the community. Weve also actively supported our growing community of entrepreneurs through in-house services, programming and events, and by providing more than $1 million in grant funding to other organizations in the region, said Fitzpatrick. In our first nine months of operating, we had 793 touchpoints with entrepreneurs. Becoming an independent organization is a natural path for us as we scale our impact building on the successful ecosystem hub models adopted by our peers in Louisville and Lexington.

Tri-ED believes this is the right evolution for Blue North.

Im confident in Brits ability to lead Blue North and build on the partnerships and the foundation weve constructed throughout the last year, said Crume. We believe this is a sustainable model for entrepreneurship services in Northern Kentucky. Blue North will continue to collaborate with our regional entrepreneurship and innovation community, which includes Tri-ED, Northern Kentucky University, Gateway Community & Technical College, Thomas More University, St. Elizabeth, CVG, the City of Covington, Cintrifuse, as well other counties, municipalities, universities, and organizations throughout the Greater Cincinnati region and Kentucky.

Blue North will continue to produce scalable impact by serving entrepreneurs and the region through the following initiatives:

Providing direct startup support services,

Creating an Industry Advisor Board to expand Blue North's access to large and mid-size corporates,

Offering expanded startup resources via the Startup Support Fellowship Fund,

Improving inclusivity and access to programming and events through the use of innovative, digital tools, and

Increasing connections with investor and capital networks.

Blue North has identified four sectors that it will focus on leveraging Northern Kentuckys unique strengths and assets: health (cancer diagnostics, screening and treatment innovations), supply chain, eCommerce, and local growth (food, beverage, distilled spirits, and creative services).

In April, Blue North announced its partnership with the New York-based The Worldwide Supply Chain Federation (TWSCF), a global grassroots community focused on connecting the companies building thesupplychaintechnologies of the future with the buyers who need them to stay competitive.Through this partnership, Fitzpatrick will lead the regions first supply chain meetup chapter to grow the regional supply chain ecosystem.

The NKY/Cincinnati region has a wealth of assets in the supply chain sector. Its the area where we see technology and innovation playing a significant role across all business sectors, as well as in the current and future growth of our ecosystem, said Fitzpatrick.

Fitzpatrick also sees providing greater access to customers as key to Blue Norths impact. Increasing B2B opportunities for entrepreneurs through collaborations with organizations like TWSCF, Cintrifuse, and CincyTech will be a win for entrepreneurs and our regional Big Cos alike.

"The Cincinnati region is deeply committed to building a world-class startup economy, said Pete Blackshaw, CEO of Cintrifuse. We congratulate Blue North on receiving the RISE grant and were committed to working alongside them to facilitate fast-track connections to Northern Kentucky startups who are addressing critical needs from supply chain and ecommerce to life sciences.

The future is bright for entrepreneurship in Northern Kentucky, said Fitzpatrick. Our partnership with the Kentucky Cabinets Office of Entrepreneurship is critical and we appreciate their continued investment and leadership as we continue to serve our regions innovators.

Fitzpatrick brings a wealth of startup and leadership experience to the Blue North team. In 2013, she founded MentorMe, one of the nation's first venture-backed SaaS mentoring startups. Before Blue North, Brit built entrepreneurship ecosystems in Memphis and led the 1804 Entrepreneur Center in Louisville, which later merged with LEAP.

Abby Ober will begin a new role as program director for Blue North. She has served as entrepreneurship Community Manager since January 2019. Leveraging her experience over the past six years, she oversees Blue Norths suite of in house-services and events while managing Blue North's grant and contract reporting.

-Staff report

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NKY Startup Community Awarded $510000 from State - The River City News

A Major Food Chain Shift Appears to Be Happening in The Arctic Right Now – ScienceAlert

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There's a major change happening in the Arctic. Dark waters are blooming with algae, as sunlight floods spaces long obscured by sheets of ice.

Over the past two decades, there's been a 57 percent increase in phytoplankton in the Arctic ocean, an analysis by researchers from Stanford University has revealed.

That's outpaced scientist's expectations, and it's changing the way the ocean stores carbon, as well as sucking up resources needed for the rest of the ecosystem. And no one's sure what it means.

"The rates are really important in terms of how much food there is for the rest of the ecosystem,"saysEarth system scientist, Kevin Arrigo.

"It's also important because this is one of the main ways that CO2is pulled out of the atmosphere and into the ocean."

At first glance this expansion of the photosynthesising part of the food chain shouldn't be all that surprising. Global warming has caused the Arctic's ice sheets to wither away over the decades, opening up new frontiers for phytoplankton to blossom.

But according to the researchers, from around 2009, the rate at which new open water was being exposed dropped off significantly.

By all accounts, this should have been followed by a similar decline in greenery. After all, no matter how much the Sun shines, population numbers should taper off as the amount of available nitrogen and other essential elements gets used up.

But that's not what happened. This expansion at the base of the food pyramid described in eco-jargon as a gain in the rate of net primary production (NPP) just kept going.

"The increase in NPP over the past decade is due almost exclusively to a recent increase in phytoplankton biomass," says Arrigo.

It's hard to know whether we should be alarmed or appreciative. After all, more green stuff means more food for herbivores, which means more meat for the carnivores.

Not to mention more carbon being locked away in organic molecules.

But the Arctic Ocean isn't really a big player when it comes to sinking carbon. Especially if vanishing sea ice simply makes way for more marine traffic.

And as Arrigo puts it, life in the Arctic is also better adapted to having plenty of ice around.

"There's going to be winners and losers," hesays.

More to the point, the extended surge in NPP observed by the team has been perplexing enough to force them to look at existing explanations and asked what they might have missed.

The study's lead author, environmental scientist Kate Lewis, explains it was initially assumed there just wasn't a big store of nutrients to chew through, a question that's been addressed previously by the team's studies.

"We knew the Arctic had increased production in the last few years, but it seemed possible the system was just recycling the same store of nutrients," says Lewis.

"Our study shows that's not the case. Phytoplankton are absorbing more carbon year after year as new nutrients come into this ocean. That was unexpected, and it has big ecological impacts."

Getting a grip on the influx of nutrients is easier said than done since it depends so much on the complexities of ocean currents spreading mixes of different materials through water columns and following trends that are also at the whim of a changing global climate.

Even just getting to this point in mapping the changes in phytoplankton required a huge rethink on how to measure the shades of colour that are traditionally used to analyse NPP.

"Algorithms that work everywhere else in the world that look at the colour of the ocean to judge how much phytoplankton are there do not work in the Arctic at all," says Arrigo.

Armed with improved, Arctic-specific processes, Lewis and her team can now be confident that the changes we're seeing in the planet's far north do point to a sustained blooming of producers fed by nutrients pouring in.

Further studies on our planet's vast circulating network of atmospheric and oceanic streams could help us better nail down what to expect of this vast algal bloom and what it means for the Arctic's future.

This research was published in Science.

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trusted computing artificial intelligence (AI) information warfare – Military & Aerospace Electronics

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ARLINGTON, Va. U.S. military researchers are reaching out to industry to prevent enemy attempts to corrupt or spoof artificial intelligence (AI) systems by subtly altering or manipulating information the AI system uses to learn, develop, and mature.

Officials of the U.S. Defense Advanced Research Projects Agency (DARPA) issued a solicitation on Wednesday (DARPA-PA-19-03-09) for the Reverse Engineering of Deceptions (RED) project, which aims at reverse engineering the toolchains of information deception attacks.

A deceptive information attack describes enemy attempts subtly to alters or manipulates information used by a human or machine learning system to alter a computational outcome in the adversarys favor.

Machine learning techniques are susceptible to enemy information warfare attacks at training time and when deployed. Similarly, humans are susceptible to being deceived by falsified images, video, audio, and text. Deception plays an increasingly central role in information warfare attacks.

Related: Research, applications, talent, training, and cooperation frame report on artificial intelligence (AI)

The Reverse Engineering of Deceptions (RED) effort will develop techniques that automatically reverse engineer the toolchains behind attacks such as multimedia falsification, enemy machine learning attacks, or other information deception attacks.

Recovering the tools and processes for such attacks provides information that may help identify an enemy. RED will seek to develop techniques that identify attack toolchains automatically, and develop scalable databases of attack toolchains.

RED Phase 1 will produce trusted-computing algorithms to identify the toolchains behind information deception attacks. The project's second phase will develop technologies for scalable databases of attack toolchains to support attribution and defense.

Related: Air Force researchers ask industry for SWaP-constrained embedded computing for artificial intelligence (AI)

The project also seeks to develop techniques that require little or no a-priori knowledge of specific deception toolchains; automatically cluster attack examples together to discover families of deception toolchains; generalize across several information deception scenarios like enemy machine learning and media manipulation; require just a few attacks to learn unique signatures; and scale to internet volumes of information.

Companies interested should upload 8-page proposals no later than 30 July 2020 to the DARPA BAA Website at https://baa.darpa.mil/. Email questions or concerns to Matt Turek, the DARPA RED program manager, at RED@darpa.mil.

More information is online at https://beta.sam.gov/opp/f108cad02f824285af5ca85e1f7481f4/view.

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trusted computing artificial intelligence (AI) information warfare - Military & Aerospace Electronics

Extra Shot: Startups and the Telecoms Ecosystem – TelecomTV

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The fifth edition of Extra Shot focuses on innovation in the telecoms industry and, in particular, the role of startups in the broader industry ecosystem, a topic that was touched upon during the recent DSP Leaders World Forum digital event.

Startups have a tough time getting funded, recognised and finding a way to get a foot in the door at the communication service providers (CSPs) and even then thats only the start of what is almost always a very long process that doesnt always deliver fruitful returns. Can this situation be rectified? Is there an alternative model and/or ecosystem for startups? Our special guests provided plenty of insight, including first-hand experience.

And, finally, co-presenters Guy Daniels and Chris Lewis were given the chance to state their caffeine preferences and take their place on the Containerized Hot Beverage Function chart

Featuring special guests:

Filmed with TelecomTVs Smart Studio service

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Extra Shot: Startups and the Telecoms Ecosystem - TelecomTV

Artificial Intelligence will aid in better decision-making capacity – Livemint

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MUMBAI :Artificial intelligence (AI) will not only help to resolve complex global problems but can enable businesses make better decisions on a day-to-day basis if applied well, said panelists at the Mint Pivot or Perish webinar on automation in the new normal post covid pandemic.

AI can be embedded into our day-to-day applications so the human intellect takes better decisions based on the most relevant data to the particular request basis past or similar requests. This is a growth opportunity for businesses now," said Dulles Krishnan, area vice president - Salesforce.

For example, during a service request, offering the employee insights about the customers preferences or similar examples of previous customers can help them efficiently up sell solutions and create more revenue or service opportunities.

On one end of automation is work that is high volume and repetitive. More usage of automation is now moving to low volume but unique work which requires solutions. That is where bots and AI solutions co-exist with humans," said Kamal Singhani, managing partner, IBM India.

Sangeeta Gupta, VP and chief strategy officer, Nasscom, said while AI can augment productivity and innovation, it can only work in well-defined use cases though it needs good quality data to work with.

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Artificial Intelligence will aid in better decision-making capacity - Livemint

COVID-19 Impact & Recovery Analysis – Artificial Intelligence Platforms Market 2020-2024 | Rise in Demand for AI-based Solutions to Boost Growth |…

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LONDON--(BUSINESS WIRE)--Technavio has been monitoring the artificial intelligence platforms market and it is poised to grow by USD 12.51 billion during 2020-2024, progressing at a CAGR of over 33% during the forecast period. The report offers an up-to-date analysis regarding the current market scenario, latest trends and drivers, and the overall market environment.

Technavio suggests three forecast scenarios (optimistic, probable, and pessimistic) considering the impact of COVID-19. Please Request Latest Free Sample Report on COVID-19 Impact

The market is concentrated, and the degree of concentration will accelerate during the forecast period. Alibaba Group Holding Ltd., Alphabet Inc., Amazon Web Services Inc., International Business Machines Corp., Microsoft Corp., Palantir Technologies Inc., Salesforce.com Inc., SAP SE, SAS Institute Inc., and Tata Consultancy Services Ltd. are some of the major market participants. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

The rise in demand for AI-based solutions have been instrumental in driving the growth of the market. However, the rise in data privacy issues might hamper market growth.

Artificial Intelligence Platforms Market 2020-2024: Segmentation

Artificial Intelligence Platforms Market is segmented as below:

To learn more about the global trends impacting the future of market research, download a free sample: https://www.technavio.com/talk-to-us?report=IRTNTR44235

Artificial Intelligence Platforms Market 2020-2024: Scope

Technavio presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources. Our artificial intelligence platforms market report covers the following areas:

This study identifies investments in AI start-ups as one of the prime reasons driving the artificial intelligence platforms market growth during the next few years.

Artificial Intelligence Platforms Market 2020-2024: Vendor Analysis

We provide a detailed analysis of around 25 vendors operating in the artificial intelligence platforms market, including some of the vendors such as Alibaba Group Holding Ltd., Alphabet Inc., Amazon Web Services Inc., International Business Machines Corp., Microsoft Corp., Palantir Technologies Inc., Salesforce.com Inc., SAP SE, SAS Institute Inc., and Tata Consultancy Services Ltd. Backed with competitive intelligence and benchmarking, our research reports on the artificial intelligence platforms market are designed to provide entry support, customer profile and M&As as well as go-to-market strategy support.

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Artificial Intelligence Platforms Market 2020-2024: Key Highlights

Table Of Contents:

Executive Summary

Market Landscape

Market Sizing

Five Forces Analysis

Market Segmentation by Deployment

Customer Landscape

Geographic Landscape

Market Drivers Demand led growth

Market Challenges

Market Trends

Vendor Landscape

Vendor Analysis

Appendix

About Us

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavios report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavios comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

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COVID-19 Impact & Recovery Analysis - Artificial Intelligence Platforms Market 2020-2024 | Rise in Demand for AI-based Solutions to Boost Growth |...

Impact of Covid-19 Outbreak on The V2X (Vehicle-to-Everything) Communications Ecosystem: 2019 2030 Opportunities, Challenges, Strategies &…

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Commonly referred to as V2X, vehicle-to-everything communications technology allows vehicles to directly communicate with each other, roadside infrastructure, and other road users to deliver an array of benefits in the form of road safety, traffic efficiency, smart mobility, environmental sustainability, and driver convenience. In addition, V2X is also helping pave the way for fully autonomous driving through its unique non line-of-sight sensing capability which allows vehicles to detect potential hazards, traffic, and road conditions from longer distances and sooner than other in-vehicle sensors such as cameras, radar, and LiDAR (Light Detection and Ranging).

Although legacy V2I (Vehicle-to-Infrastructure) technologies are currently in operational use worldwide for ETC (Electronic Toll Collection) and relatively simple V2I applications, advanced V2X systems capable of supporting V2V (Vehicle-to-Vehicle), V2I and other forms of V2X communications are beginning to gain broad commercial acceptance with two competing technologies vying for the attention of automakers and regulators: the commercially mature IEEE 802.11p/DSRC (Dedicated Short Range Communications) standard, and the relatively new 3GPP-defined C-V2X (Cellular V2X) technology which has a forward evolutionary path towards 5G.

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With an initial focus on road safety and traffic efficiency applications, Toyota and GM (General Motors) have already equipped some of their vehicle models with IEEE 802.11p-based V2X technology in Japan and North America. Among other commercial commitments, Volkswagen will begin deploying IEEE 802.11p on volume models in Europe starting from 2019, while Geely and Ford plan to integrate C-V2X in their new vehicles by 2021 and 2022 respectively. It is also worth nothing that a number of luxury automakers including BMW, Daimler, Volkswagens subsidiary Audi, and Volvo Cars already deliver certain V2X-type applications through wide-area cellular connectivity and supporting infrastructure such as appropriately equipped roadwork trailers.

Despite the ongoing 802.11p/DSRC versus C-V2X debate, regulatory uncertainty and other challenges, global spending on V2X communications technology is expected to grow at a CAGR of more than 170% between 2019 and 2022. SNS Telecom & IT predicts that by the end of 2022, V2X will account for a market worth $1.2 Billion, with an installed base of nearly 6 Million V2X-equipped vehicles worldwide.

The V2X (Vehicle-to-Everything) Communications Ecosystem: 2019 2030 Opportunities, Challenges, Strategies & Forecasts report presents an in-depth assessment of the V2X ecosystem including market drivers, challenges, enabling technologies, application scenarios, use cases, business models, key trends, standardization, spectrum availability/allocation, regulatory landscape, V2X deployment case studies, opportunities, future roadmap, value chain, ecosystem player profiles and strategies. The report also presents market size forecasts from 2019 till 2030. The forecasts cover four submarkets, two air interface technologies, 10 application categories and five regions.

The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

Topics Covered

The report covers the following topics:

Forecast Segmentation

Market forecasts are provided for each of the following submarkets and their subcategories:

Submarkets

Air Interface Technologies

Application Categories

Regional Markets

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Key Questions Answered

The report provides answers to the following key questions:

Key Findings

The report has the following key findings:

Countires Covered

List of Companies Mentioned

For More Information Kindly Contact:ResearchMozMr. Rohit Bhisey,90 State Street,Albany NY,United States 12207Tel: +1-518-621-2074USA-Canada Toll Free: 866-997-4948Email:[emailprotected]Media Release @https://www.researchmoz.us/pressreleaseFollow me on Blogger:https://trendingrelease.blogspot.com/

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Impact of Covid-19 Outbreak on The V2X (Vehicle-to-Everything) Communications Ecosystem: 2019 2030 Opportunities, Challenges, Strategies &...

The V2X (Vehicle-to-Everything) Communications Ecosystem: 2019 2030 Opportunities, Challenges, Strategies & Forecasts – 3rd Watch News

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V2X (Vehicle-to-Everything) Communications Marketresearch Report is a valuable supply of perceptive information for business strategists. This V2X (Vehicle-to-Everything) Communications Market study provides comprehensive data which enhances the understanding, scope and application of this report.

A specific study of competitive landscape of the global V2X (Vehicle-to-Everything) Communications Market has alloted, providing insights into the corporate profiles, financial standing, recent developments, mergers and acquisitions, and therefore the SWOT analysis. This analysis report will give a transparent conceive to readers concern regarding the overall market situation to further choose on this market projects.

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The V2X (Vehicle-to-Everything) Communications Market report profiles the following companies, which includes:

This report studies the global V2X (Vehicle-to-Everything) Communications Market status and forecast, categorizes the global V2X (Vehicle-to-Everything) Communications Market size (value & volume), revenue (Million USD), product price by manufacturers, type, application, and region. V2X (Vehicle-to-Everything) Communications Market Report by Material, Application and Geography with Global Forecast to 2030 is an connoisseur and far-reaching research provide details related to worlds major provincial economic situations, Concentrating on the principle districts (North America, South America Europe, and Asia-Pacific) and the crucial nations (United States, Germany, United Kingdom, Japan, South Korea, and China).

Market Segment by Type : Type 1, Type 2

Market Segment by Applications : Applications 1, Applications 2

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Table of Contents

Global V2X (Vehicle-to-Everything) Communications Market Size, Status and Forecast 20301 Market Overview2 Manufacturers Profiles3 Global V2X (Vehicle-to-Everything) Communications Sales, Revenue, Market Share andCompetitionby Manufacturer4 Global V2X (Vehicle-to-Everything) Communications Market Analysis by Regions5 North America V2X (Vehicle-to-Everything) Communications by Countries6 Europe V2X (Vehicle-to-Everything) Communications by Countries7 Asia-Pacific V2X (Vehicle-to-Everything) Communications by Countries8 South America V2X (Vehicle-to-Everything) Communications by Countries9 Middle East and Africa V2X (Vehicle-to-Everything) Communications by Countries10 Global V2X (Vehicle-to-Everything) Communications Market Segment by Type11 Global V2X (Vehicle-to-Everything) Communications Market Segment by Application12 V2X (Vehicle-to-Everything) Communications Market Forecast13 Sales Channel, Distributors, Traders and Dealers14 Research Findings and Conclusion15 Appendix

Overview of the chapters analysing the global V2X (Vehicle-to-Everything) Communications Market in detail:

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The V2X (Vehicle-to-Everything) Communications Ecosystem: 2019 2030 Opportunities, Challenges, Strategies & Forecasts - 3rd Watch News