Using pictures of their organs, a new computer program can predict patients’ lifespans.

Researchers from the University of Adelaide’s School of Public Health and School of Computer Science analyzed the medical imaging of 48 patient’s chests and used a computer-based analysis 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,” lead author Dr. Luke Oakden-Rayner, a radiologist and Ph.D. student with the University of Adelaide’s School of Public Health, said in a statement. “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 explained how the computer system 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. “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 demonstrates that radiomics techniques can be used to extract biomarkers relevant to one of the most widely used outcomes in epidemiological and clinical research—mortality and deep learning with convolutional neural networks can be applied to radiomics research.

Radiomics is the use of high-throughput computational techniques to analyze the high-dimensional data of medical images.  

The researchers placed the most confidence in the computer’s predictions for patients with severe chronic diseases including emphysema and congestive heart failure.

Oakden-Rayner said instead of diagnosing diseases the system can predict medical outcomes by incorporating large volumes of data and detecting subtle patterns, which 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.

The future of this technology may include the ability to predict other medical conditions including the onset of heart attacks.

The study was published in Scientific Reports.