Daily Archives: February 15, 2022

Its easy to miss good news amid coverage of the pandemic, the rising cost of living and the, ahem, rest. However, the United Kingdom is getting something right.

On Thursday, the government announced that it is investing up to 23m to boost artificial intelligence (AI) skills by creating up to 2,000 scholarships across England. This will fund masters conversion courses for people from non-Stem (science, technology, engineering and mathematics) degrees.

This will attract a less homogeneous group, explains Tabitha Goldstaub, who chairs the governments AI council and advises the Alan Turing Institute, which means the UK AI ecosystem benefits from graduates with different backgrounds, perspectives and life experiences.

This investment in widening education and opportunity is just one of several steps in the 10-year AI national strategy, which aims to make Britain a world leader in AI. Were not the only ones; as the AI dashboard at the Organisation for Economic Development (OECD) shows, many other countries have their eye on the same prize.

The frontrunners in this race, the United States and China, have bigger populations and deeper pockets, while the European Union has an impressive record in setting global norms and rules for data protection. To have any hope of keeping up, at the very least the UK must find a way to punch above its weight.

The signs are promising. AI is already an unstoppable force in our economy. According to Tech Nation, there are more than 1,300 AI companies in the United Kingdom. Research commissioned by the government and published last month shows UK businesses spent around 63bn on AI technology and AI-related labour in 2020 alone. This figure is expected to reach more than 200bn by 2040, when it is predicted more than 1.3m UK businesses will be using AI.

Even so, to make the most of the opportunities that this offers and to understand the risks we will need to upgrade how we educate and train our workforce. This will be tricky because AI is surrounded by a lot of hype and mixed messages. Depending on whos talking, AI will be a more profound change than fire or electricity (Google CEO, Sundar Pichai), it could spell the end of the human race (Professor Stephen Hawking) or help us save the environment, cure disease and explore the universe (Demis Hassabis, founder of London-based DeepMind).

Some AI researchers strike a more cautious tone, arguing that AI is just statistics on steroids (Dr Meredith Broussard) and neither artificial nor intelligent (Dr Kate Crawford). All agree that AI is transforming how we work, live, wage war and even understand what it means to be human, as Professor Stuart Russell explored in his BBC Reith Lectures in December.

As we aim for the goal of becoming a world leader in AI, the United Kingdom must choose between putting ethics at the core of our strategy or leaving it as an option a bolt-on at best. This is not a choice between being unethical or ethical; rather, it reflects a fear that regulation risks stifling innovation, especially if other countries do not prioritise ethics in their approach to AI.

However, ethics is about more than laws and regulations, compliance and checklists. Its about designing the world we want to live in. As Sir Tim Berners-Lee, who created the world wide web, explained in 2018: As were designing the system, were designing society Nothing is self-evident. Everything has to be put out there as something that we think will be a good idea as a component of our society.

Again, he was ahead of his time. A new role is emerging in our economy: technology ethicist. Its contours are still being shaped. Is it a technologist who works in ethics? An ethicist who works in technology? Can anyone call themselves a technology ethicist or is it an anointed position?

Rather than focus on what technology ethicists are, lets consider what they do. They might have trained in the law, data science, design or philosophy or as artists and designers. They might be employed by universities (and not just in the philosophy and computer science departments) or work in thinktanks, NGOs, private companies or any part of government. They may infuse new meaning into existing roles, such as researcher, software developer and project manager. Or they might have new responsibilities, such as responsible AI lead, algorithmic reporter or AI ethicist.

They are working daily to ensure that government websites are accessible to all UK inhabitants or fighting to force the government to reveal the algorithm it is using to identify disabled people as potential benefit fraudsters, subjecting them to stressful checks and months of frustrating bureaucracy. They are doing open-source intelligence investigations into crime, terrorism and human rights abuses, or improving healthcare delivery, or protecting children online. They are working in virtual reality and augmented reality and building and warning about the metaverse.

Some of the leading technology ethicists in the world were either educated and trained in the UK or are living and working here now. This presents us with a unique opportunity to draw on their talents to ensure that ethics is embedded into our AI strategy, rather than treated as an elective or a bolt-on.

This is about more than redesigning our education curriculum or new ways of working. Its about creating the future.

Stephanie Hare is a researcher and broadcaster. Her new book is Technology Is Not Neutral: A Short Guide to Technology Ethics

Read more:

The rise of AI could be a great British story. But let's do it the right way - The Guardian

Feb. 15, 2022 07:00 UTC

SEOUL, South Korea--(BUSINESS WIRE)-- Genuv, Inc., a clinical-stage biotechnology company focused on innovative drug discovery for central nervous system disorders and developing advanced antibody therapies, announced an agreement with the medical technology company Aiforia Technologies Plc, to add Aiforias AI deep learning for medical image analysis to its ATRIVIEW discovery platform.

The new version, ATRIVIEW AI, will seamlessly incorporate Aiforias deep learning artificial intelligence technology to speed and automate image analysis within Genuvs ATRIVIEW drug discovery platform. ATRIVIEW AI will enable faster drug discovery and simultaneous analysis of multiple biomarkers.

Aiforia is helping Genuv bring the power of deep learning artificial intelligence to our unique ATRIVIEW drug discovery platform, said Sungho Han, Ph.D., founder and CEO of Genuv. The additional speed will enable Genuv and our partners to bring more drug candidates to the clinic more quickly.

ATRIVIEW is Genuvs proprietary drug discovery platform. It is used to screen both existing drugs and new substances for neuroprotective and neurogenerative effects. Genuvs lead drug candidate, SNR1611, was discovered with ATRIVIEW. SNR1611 has been shown to restore CNS functions in preclinical models of amyotrophic lateral sclerosis (ALS) and Alzheimers Disease. It is now being studied in a Phase1/2a clinical trial for ALS.

Aiforias image analysis tools are used by many major pharmaceutical and biotechnology firms, including Sanofi, Boehringer Ingelheim, AstraZeneca and Bristol Myers Squibb, to help translate images into discoveries, decisions and diagnoses. Aiforia frees scientists and researchers from laborious manual tasks such as counting individual cells in diagnostic images.

The partnership with Genuv marks the first time Aiforias technology is being used in neuroscience drug discovery for neurodegenerative diseases such as ALS and Alzheimers disease.

Were excited to help Genuv extend the capabilities of the remarkable ATRIVIEW platform with the help of our powerful, deep learning technology, said Jukka Tapaninen, CEO of Aiforia Technologies Plc. Aiforia brings increased efficiency and precision to medical image analysis in fields including neuroscience. ATRIVIEW is a powerful approach to the enormous unmet need in neurodegenerative diseases and we are humbled to be a part of this collaboration.

ABOUT GENUV Genuv Inc. is a leader in discovering drugs for central nervous system (CNS) disorders and advanced antibody therapies. The ATRIVIEW drug screening platform uses cell phenotypic and biomarker analyses to discover substances for the development of neurodegenerative disease treatment. The companys SHINE MOUSE and NuvoMabTM platform generate antibodies with superior affinity, solubility, and stability. Based in Seoul, Korea, Genuv launched its first clinical trial in Korea in 2020. Genuv uses scientific imagination and unique platform technologies to overcome the challenges in debilitating diseases. Learn more at http://www.genuv.com.

ABOUT ATRIVIEW and ATRIVIEW AI ATRIVIEW AI is the next generation of ATRIVIEW, Genuvs proprietary CNS drug screening platform. ATRIVIEW technology helps Genuv and its partners to discover CNS drug candidates that preserve homeostasis in the brain and induce adult neuronal stem cells to develop into neurons. Genuv believes that neuroprotection and neurogenesis are key to treating Alzheimers Disease, amyotrophic lateral sclerosis (Lou Gehrigs disease), and other neurodegenerative diseases. Compared to ATRIVIEW, ATRIVIEW AI uses fewer resources to process large quantities of data generated during screening, speeding the discovery of drug candidate hits. ATRIVIEW and ATRIVIEW AI explore the full spectrum of screened substances for potential use as CNS drugs candidates.

ABOUT AIFORIA TECHNOLOGIES PLC Aiforia equips pathologists and scientists in preclinical and clinical labs with powerful deep learning artificial intelligence software for translating images into discoveries, decisions, and diagnoses. The cloud based Aiforia products and services aim to escalate the efficiency and precision of medical image analysis beyond current capabilities, across a variety of fields from oncology to neuroscience and more. Find out more at aiforia.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20220214005885/en/

View post:

Genuv Teams With Aiforia to Create an AI-Powered Version of its ATRIVIEW Drug Screening Platform - BioSpace

Baheya Foundation an Egyptian non-profit that provides breast cancer treatment free of charge has partnered with GE Healthcare to explore the use of artificial intelligence (AI) to improve outcomes in patients.

According to GE Healthcare, it is working with the foundation and its hospital to develop and validate the use of AI to assess and predict the response of neoadjuvant therapy in locally advanced breast cancer.

Usually the first step in treatment, neoadjuvant therapy is used to help shrink tumours, prior to main treatment such as surgery. Examples include chemotherapy, radiation therapy, and hormone therapy.

We are enthusiastic about how this research collaboration has the potential to transform future outcomes for breast cancer patients, said Agnes Berzsenyi, President and CEO of Womens Health at GE Healthcare. By combining our expertise with that of the Baheya Foundation and layering it with AI, we are one step closer to delivering on our mission of increasing early detection and helping to save more lives.

THE LARGER CONTEXT

With a number of diagnostic imaging technologies used to predict and assess a patients response to neoadjuvant therapy, AI reportedly has the potential to offer clinicians an earlier indication of how well a patient is responding to the treatment. This allows a timely change of treatment, with a reduction in unnecessary toxicity to the patient and a lower treatment cost for the hospital, explained GE Healthcare.

The company added that the project will focus on the use of AI in contrast-enhanced spectral mammography (CESM).

WHY IT MATTERS

Baheya Foundation confirmed that, as it grows its operations and expands the number of patients it serves, its new collaboration with GE Healthcare aims to expand clinical treatment options and further improve patient outcomes and experiences.

Founded in 2015, Baheya Foundation was formed in tribute to Baheya Wahbi, who when diagnosed with breast cancer herself over 20 years ago was not able to find treatment in Egypt. Honouring her request prior to her passing, her family went on to set up the non-profit to ensure all women in Egypt, no matter their income level, had access to world-class cancer care.

Every month, Baheya Hospital manages around 7,000 early detection incidences of breast cancer, 1,500 chemotherapy sessions, 3,000 radiation therapy sessions, and 350 surgeries. A second hospital is planned to open in Cairos Sheikh Zayed City in 2023.

ON THE RECORD

In addition to providing direct care to women, Baheya Foundation also conducts research to continually enhance the services it offers, said Mohamed Emara, CEO of Baheya Hospital. Baheya is [a] centre of excellence, providing [the] most advanced technology, [keeping] pace with global developments. [It is a] unique hospital in Egypt and [the rest of the] MENA region.

Radio-diagnosis consultant Mohamed Gomaa, who is the hospitals Head of Radiology, added: As part of our commitment to ongoing research in this field, our collaboration with GE Healthcare seeks to deploy the power of AI combined with clinical experience to expand our knowledge of the treatment pathways for neoadjuvant therapy to improve outcomes for patients at Baheya and beyond.

Link:

Baheya Foundation explores AI to predict response to breast cancer treatment - Mobihealth News

From ensemble cast of authors former Secretary of State Henry Kissinger, former Google CEO Eric Schmidt and MITs Daniel Huttenlocher comes The Age of AI: And Our Human Future, an exploration of how artificial intelligence (AI) is already changing our world and how it may someday change the very nature of the human condition.

AI will affect everything from the way we make scientific discoveries to the way warfare is conducted, the authors predict. It has already surpassed the worlds greatest chess players, and it wont be long before AI algorithms are the safest drivers on the road, the sharpest medical diagnosticians or the most prolific artists and writers.

But, uncontrolled, AI also poses nightmarish dangers to society: producing hyper-realistic fake speeches or videos of events that never happened, AI-driven warfare spilling over into the civilian sphere, or, most disturbingly, a future where the most significant decisions about the fate of the world are not made by humans.

While I had some familiarity with the subject of AI, I was excited to develop a well-rounded understanding of it from this title.

The Age of AI: And Our Human Future is dense with explanations, predictions, opinions and fears about AI, and is also encased in difficult and, at times, repetitive language. It lays out rough outlines for national and global committees that should determine AIs uses and limitations across industry, academia and governments, in what feels like a stream of consciousness narrative.

Because this book is based on actual conversations between the authors, it felt at times as if I were being hit with the conclusions of many hours of thought without the time to reason through it all myself and keep pace.

But the abstruse wording and repetitive statements werent the biggest obstacles to getting through this book. Instead, it was the deeply thought-provoking points made by the authors that regularly sent me spiraling into reflection. The authors did succeed in what was perhaps their primary objective: to instill in the reader a sense of the significance of AI and the need for discourse about it.

This book ambitiously attempts to walk the reader through as comprehensive a summary of AI as can be fit in 143 pages. This book has convinced me that AI will span far beyond the domain of science and technology, infiltrating every aspect of society and changing nearly everything about the way we live our lives.

Although I expected to come away from the reading somewhat satisfied on the subject, I was left asking more questions than I could find answers for in these pages. Though it was my first book on the subject, it will certainly not be the last.

This book may not be the singular text about artificial intelligence that I was hoping for, but its worth reading nonetheless. Its a guidebook for the kind of considerations we should be having about AI: how it will impact the economy, law, warfare, diplomacy and what it will mean to be human in a world dominated by nonhuman intelligence.

At its core, this book is meant to start a conversation perhaps what will soon be the conversation. As a new, AI-driven epoch of human existence looms on the horizon, this is a subject everyone needs to take the time to familiarize themselves with the sooner, the better. To that end, one need not look further than The Age of AI: And Our Human Future to do just that.

Go here to see the original:

Book Review: 'The Age of AI: And Our Human Future' - The Montclarion

This study evaluated if AI could determine the positional relationship between M3 and IAN based on panoramic radiography regarding whether the two structures were in contact or intimate and whether the IAN was positioned lingually or buccally to M3 when two structures were overlapped. In this situation, determining the exact position was limited and unreliable even for the specialist, as shown in previous studies25,26. However, AI could determine both positions more accurately than OMFS specialists.

Until now, if M3 and IAN overlap on panoramic radiograph, specialists could use the known predictive signs of IAN injury to determine the positional relationship whether the two structures were in contact or intimate. Umar et al. compared the positional relationship between IAN and M3 through panoramic radiography and CBCT. Loss of the radiopaque line and diversion of the canal on panoramic radiographs resulted in tooth and nerve contact in 100% of the cases on CBCT. Darkening of the roots were associated with contact on CBCT in 76.9% of the cases studied27. However, another study reported that the sensitivities and specificities ranged from 14.6 to 68.3% and from 85.5 to 96.9%, respectively, for those three predictive signs1. Datta et al. compared those signs with the clinical findings during surgical removal and found that only 12% of patients with positive radiological signs showed clinical evidence of involvement3. In the present study, we adopted CBCT reading results instead of radiological signs on panoramic radiography to determine the positional relationship so that the AI could determine whether the two structures were in contact or intimate, showing an accuracy of 0.55 to 0.72. Compared to another study1, our deep learning model exhibited similar performance (accuracy 0.87, precision 0.90, recall, 0.96, F1 score 0.93, and AUC 0.82) to determine whether M3 is contacting the IAN or not. This could explain the different model performance depending on the characteristics of the data.

To replace CBCT with analysis of panoramas with AI, information about bucco-lingual positioning was necessary to ensure safe surgical outcomes. It has been reported that the lingual position of the nerve to the tooth has a significantly higher risk of IAN injury compared to other positions28. To the best of our knowledge, no studies have evaluated bucco-lingual positioning through panoramic radiograph because there were no methods to predict this position using one radiograph. Two intraoral radiographs with different angle (vertical tube-shift technique) in the third molar area caused patient discomfort and nausea during placement of the film or sensor of the digital intraoral x-ray devices29 and is difficult to use clinically. Since there was no effective method to discern the position, the accuracy of the specialists was low in this study. On the contrary, the AI showed considerably high accuracy ranges from 67.7 to 80.6% despite the small amount of study data. The course of the IAN predominantly is buccal to the tooth28, and our data revealed a similar situation. However, the total number of cases was small to match the numbers in each group evenly for deep learning. In addition, the lack of total number of cases forced the use of a simple deep learning model with a relatively small number of parameters to be optimized. Therefore, training AI with more data could produce more accurate results and be used more widely in clinical settings.

In this study, bucco-lingual determination (Experiment 2) exhibited superior performance for true contact positioning (Experiment 1). The difference in accuracy between the two experiments seems to be a characteristic of the data rather than a special technical difference. There might be a particular advantage for AI to be recognized in bucco-lingual classification, or that some of the contact classification data might have characteristics that are difficult to distinguish.

There are several studies that have developed Al algorithms that have been able to outmatch specialists in terms of performance and accuracy. AI assistance improved the performance of radiologists in distinguishing coronavirus disease 2019 from pneumonia of other origins in chest CT30. Moreover, the AI system outperformed radiologists in clinically relevant tasks of breast cancer identification on mammography31. In the present study, the AI exhibited much higher accuracy and performance compared to those of OMFS specialists. To determine the positional relationship between M3 and IAN, we performed preliminary tests to determine the most suitable AI model using VGG19, DenseNet, EfficientNet, and ResNet-50. ResNet showed higher AUC in Experiment 2 and comparable AUC in Experiment 1 (Supplemental Tables 13). Therefore, it was chosen as the final AI model.

This study has limitations. First, the absolute size of the training dataset was small. Data augmentation by image modification was used to overcome the limitation of a small sized dataset. Nevertheless, as shown in Table 1, there were cases where training did not proceed robustly. Therefore, the performances of the trained models highly depend on the train-test split. This unsoundness of the trained model, which hinders the clinical utility of AI models for primary determination in practice, can be alleviated by collecting more data and using them for training. Also, the size of deep learning models is an important factor in performance and, in general, a large number of instances are required to train a large size deep neural network without overfitting. Thus, not only collecting more data but also exploiting external datasets from multiple dental centers can be considered to increase the performance of AI models. However, this study is meaningful in that the AI model performed better than experts even under these adverse conditions. Second, the images used in this study were cropped without any prior domain knowledge such as proper size or resolution to include sufficient information to determine true contact or bucco-lingual positional relationship between M3 and IAN. If the domain knowledge is reflected to construct a dataset, the performances of AI models can be highly increased. Third, the use of interpretable AI models32, which can explain the reason for the model prediction, can help to identify the weaknesses of the trained models. The identified weaknesses can be overcome by collecting data that the models have difficulty in classifying. Finally, the various techniques developed in the machine learning society, such as ensemble learning33, self-supervised learning34, and contrastive learning35, can be utilized for further improvement of the performance of our models even in situations where the total number of cases is insufficient as well.

Read more:

Artificial intelligence in positioning between mandibular third molar and inferior alveolar nerve on panoramic radiography | Scientific Reports -...

Leading global AI-powered credit decision platform provider, Scienaptic AI announced that deployment of its platform at Northern Credit Union is now live.

This deployment will enhance and augment Northern Credit Unions credit decisioning and underwriting capabilities for new and prospective members.

Founded in 1955 by a group of New York Air Brake employees, Northern Credit Union serves more than 36,000 members through nine Relationship Center locations across the North Country and a comprehensive online and mobile banking program. Throughout its history, Northern Credit Union has helped its members by providing the financial services, resources and education they need to achieve their financial goals. From its beginning and far into its future, this has been and will remain Northern Credit Union's foremost commitment.

As an organization that aspires to be the recognized standard of excellence in all our markets, we humbly embrace the higher expectations and responsibility to continuously improve for the betterment of our members, said Dan St. Hilaire, CEO at Northern Credit Union. Northern is blessed to have partnered with a forward-thinking organization whose mission, vision and culture, uniquely aligns with ours. Working with Scienaptic has been effortless, educational and a whole lot of fun! Our collaborative success will be premised on this foundational advantage. We are excitedly eager to release our pent-up excitement for the profound impact this platform will surely have on the financial well-being of our members and organization.

"We are driven to improve the financial lives of members Northern Credit Union serves through credit empowerment and personalized decisions, said Pankaj Jain, Co-founder and President of Scienaptic. In our shared passion to WOW members and exceed their expectations, we feel privileged that our AI is increasing credit access and supporting Northern Credit Union members in fulfilling their dreams.

See more here:

Northern Credit Union goes live with Scienaptic AI platform - Finextra

CHARLOTTE Channel 9 got an early look at first-of-its kind technology thats designed to keep drivers and passengers safe on the highway.

Part of Interstate 77 will soon have so-called smart cameras. Theyll be used to help alert crews to any dangers on the drive through the 26 miles of toll lanes between uptown Charlotte and Mooresville.

Traffic Team 9s Mark Taylor visited the Charlotte Traffic Management Center with Channel 9s partners at I-77 Mobility to see how they work.

[ALSO READ: Why are deadly crash trends on the rise around Charlotte?]

Heath Holland is the manager of the CTMC.

Once we pull the incident up on camera and verify it is an actual incident, the operator is trained at that point to dispatch necessary emergency crews, Holland said.

The system is impressive but it can be overwhelming to manage. A new pilot program using artificially intelligent cameras along I-77 could alert crews to danger more quickly.

AI technology isnt totally new, but the new pilot has the first cameras of their kind in North Carolina and the technology is remarkable.

What we want to look for is the past and present images to be constantly moving, said I-77 Mobility Chief Information Officer Farouk Soliman. Any changes when something is not moving, the system goes thats a problem. Or it will see something that wasnt there in the previous image and it senses something there that is new.

[ALSO READ: SC motorcycle deaths reach four-decade high of 154 in 2021]

Thats when emergency services are alerted, getting first responders to those hazards faster. That shorter response time could save lives.

But the new cameras arent cheap; they can cost up to $8,000 apiece. But whos paying?

This does not cost motorists anything, Soliman said. This is part of our budget to maintain the road safe for everyone.

And I-77 Mobility said it will be worth it. Last year, crews responded to more than 2,200 incidents -- 950 of them crashes. The numbers show a decline in the previous three years, but it wants those numbers to reach zero.

Our goal is to always have the latest in innovation out there to make sure the road is safe for our motorists, Soliman said.

Mobility Partners hopes to have a significant number of cameras installed along the 26-mile corridor by the end of the year. The cameras will be installed in stages, starting with sections of I-77 that see higher traffic volumes and accident-prone areas, like on- and offramps.

(WATCH BELOW: Expect officers to crack down on fast drivers along Charlottes speed corridors)

2022 Cox Media Group

Here is the original post:

I-77 will have smart cameras that use AI to alert first responders to crashes - WSOC Charlotte

In the second half of 2021 the number of artificial intelligence deals decreased significantly by 50% from the same period in 2020.

This marks an acceleration in growth from the 75% decrease in deals that occurred in H1 2021 relative to the same period a year earlier.

GlobalDatas deals database looks at mergers, acquisitions and venture capital and private equity investments taking place daily between thousands of companies across the world.

During second half of 2021, artificial intelligence deals accounted for 2.2% of all deals taking place in the sector. This represents an increase from the figure of 2% in second half of 2020.

GlobalData's thematic approach to sector activity seeks to group key company information on investments to see which industries are best placed to deal with any issues they may encounter.

These themes, of which artificial intelligence is one, are best thought of as "any issue that keeps a CEO awake at night", and by tracking them, it becomes possible to ascertain which companies are leading the way on specific issues and which ones have some work to do.

ATM Systems, Simulators and Tools

More here:

AI deals decreased significantly in the airport industry in H2 2021 - Airport Technology