If you could look into a crystal ball to learn when you’ll die, would you?
Scientists at Australia’s University of Adelaide have developed an artificial intelligence system that can predict a patient’s lifespan.
Analyzing medical imaging of 48 subjects’ chests, the computer was able to forecast—with 69 percent accuracy—who would pass away within five years. That’s comparable to “manual” prognosis by clinicians, according to the University.
“The accurate assessment of biological age and the prediction of a patient’s longevity has so far been limited by doctors’ inability to look inside the body and measure the health of each organ,” Luke Oakden-Rayner, a radiologist and Ph.D. student, said in a statement.
So he teamed up with researchers from the University’s School of Public Health and School of Computer Science to test “deep learning,” an AI technique that teaches computers how to understand and analyze images.
“Predicting the future of a patient is useful because it may enable doctors to tailor treatments to the individuals,” Oakden-Rayner said.
It remains unclear exactly what the computer detected in the images that led to those conclusions. But the most confident guesses were made for patients suffering severe chronic diseases like emphysema and congestive heart failure.
This technique, according to Oakden-Rayner, allows the automated system to predict medical outcomes “in a way that doctors are not trained to do”—by incorporating large volumes of data and detecting subtle patterns.
“Although for this study only a small sample of patients was used, our research suggests that the computer has learned to recognize the complex imaging appearances of diseases, something that requires extensive training for human experts,” the doctor said.
Researchers hope to apply the same techniques to predict other important medical conditions, including the onset of heart attacks. The next stage of their work involves analyzing tens of thousands of patient images.
“Our research opens new avenues for the application of artificial intelligence technology in medical image analysis,” Oakden-Rayner boasted. “And could offer new hope for the early detection of serious illness, requiring specific medical interventions.”
Check out the full study online, published last month in the Nature journal Scientific Reports.
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