Want to know if youll be dead in five years? Just let a computer look at your organs. <\/p>\n
New research has indicated that future predicting computers could be coming to hospitals in the near future. Researchers are hoping that the technology could be used to predict serious illnesses and medical conditions such as heart attacks. <\/p>\n
For the study, five yearold medical images of 48 patients chests were analyzed by artificial intelligence. From these images alone, the system was able to predict (with 69 percent accuracy) whether or not a patient would die within five years. It was also able to predict medical outcomes by analyzing large volumes of data and discovering subtle patterns. This new exambyAI has proven to be more effective than a physical exam from a doctor, though apparently its really not a fair fight. <\/p>\n
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Human doctors are not trained to predict mortality, so the comparison is a bit unfair, study leader Dr. Luke OakdenRayner of the University of Adelaide told Fox News. OakdenRayner added that previous research using clincial data such as age, sex or physical fitness had between 65 percent and 75 percent accuracy, so the new study \"compare[s] favorably, especially considering we excluded factors like age and sex from our analysis.\" <\/p>\n
Currently the system is only trained to predict death within five years, although, according to OakdenRayner, with the right dataset it should be trivial to extend the technique to other time scales. <\/p>\n
To predict mortality at ten years, for example, the system would need to analyze CT scans performed over ten years ago so that OakdenRayners team could have the follow up results. The researchers also couldnt tell what exactly it was the computers were seeing in the images to make their assessment, though they did find a strong relationship between the prediction of mortality and the presence of visible illnesses such as emphysema and congestive heart failure. <\/p>\n
OakdenRayner explained that certain techniques could be applied to visualize how the computers were seeing the scans, but the study was too small to use them this goround. <\/p>\n
You can identify the regions of the images that contributed to the prediction, and you can hallucinate images that exaggerate the features that the system uses (generating exemplars of \"survival\" and \"mortality\" scans), he said. We couldn't apply these techniques effectively due to our small dataset, but are currently applying them to a much larger group consisting of tens of thousands of patients. <\/p>\n
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For this next round of testing, OakdenRayner and his team will be incorporating highly predictive clinical information like age and sex into their models, which they expect will improve prediction accuracy. <\/p>\n
Similar medical AI news has been cropping up lately: a startup in China revealed an AI system that can help doctors identify lung cancer by examining CT scans, and IBM now has AI in hospitals (called Watson) that can answers patient questions. However, if perfected, this new medical AI could be the most exciting development yet. <\/p>\n
We will start looking at predicting other medical events before they happen, like strokes, cancer and heart attacks, OakdenRayner said. <\/p>\n
The study can be found in \"Scientific Reports.\" <\/p>\n
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