AI Can Now Predict Patients' Lifespans With 69% AccuracyAI Can Now Predict Patients' Lifespans With 69% Accuracy
AI Can Now Predict Patients' Lifespans With 69% Accuracy
June 2, 2017
Researchers from the University of Adelaide have used image recognition to predict, with 69 percent accuracy, which patients would die within five years.
Researchers from the University of Adelaide’s School of Public Health and School of Computer Science have used a new computer program with can help to predict patients' lifespans via AI and image recognition. Using this technology, they were able to predict with 69 percent accuracy which patients would die within five years.
“Predicting the future of a patient is useful because it may enable doctors to tailor treatments to the individual,” said Dr. Luke Oakden-Rayner, a radiologist and Ph.D. student at the University of Adelaide's School of Public Health. “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.”
Oakden-Rayner went on to explain how the computer system actually works. “Our research has investigated the use of 'deep learning,’ a technique where computer systems can learn how to understand and analyze images,” he said in a statement. “Although for this study only a small sample of patients was used, our research suggests that the computer has learnt to recognize the complex imaging appearances of diseases, something that requires extensive training for human experts.”
The study published in Scientific Reports demonstrated how radiomics and deep learning techniques can be deployed in tandem to help analyse data within medical images. The researchers placed the most importance on the computer’s predictions for patients with severe chronic diseases such as emphysema and congestive heart failure.
Oakden-Rayner highlighted how their new system can predict medical outcomes within 69 percent by incorporating large amounts of data and spotting small patterns instead of diagnosing the diseases themselves. This is something that doctors are unable to do.
“Our research opens new avenues for the application of artificial intelligence technology in medical image analysis and could offer new hope for the early detection of serious illness, requiring specific medical interventions,” he said.
This technology may very well be able to predict things such as heart attacks, which would be hugely beneficial in healthcare.
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