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Artificial intelligence plays part in Adelaide Uni medical research

A computer's ability to predict a patient's lifespan simply by looking at images of their organs is a step closer to becoming a reality due to new research led by the University of Adelaide.

The research, now published in the Nature journal Scientific Reports, is said to have implications for the early diagnosis of serious illness, and medical intervention.

Researchers from the University's School of Public Health and School of Computer Science, along with Australian and international collaborators, used artificial intelligence to analyse the medical imaging of 48 patients' chests.

The computer-based analysis was able to predict which patients would die within five years, with 69% accuracy – comparable to "manual" predictions by clinicians.

Nature says this is the first study of its kind using medical images and artificial intelligence.

"Predicting the future of a patient is useful because it may enable doctors to tailor treatments to the individual," says lead author Dr Luke Oakden-Rayner, a radiologist and PhD student with 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.

"Our research has investigated the use of 'deep learning', a technique where computer systems can learn how to understand and analyse images.

"Although for this study only a small sample of patients was used, our research suggests that the computer has learnt to recognise the complex imaging appearances of diseases, something that requires extensive training for human experts," Dr Oakden-Rayner says.

According to Nature, while the researchers could not identify exactly what the computer system was seeing in the images to make its predictions, the most confident predictions were made for patients with severe chronic diseases such as emphysema and congestive heart failure.

"Instead of focusing on diagnosing diseases, the automated systems can predict medical outcomes in a way that doctors are not trained to do, by incorporating large volumes of data and detecting subtle patterns," Dr Oakden-Rayner says.

"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."

The researchers have said they hope to apply the same techniques to predict other important medical conditions, such as the onset of heart attacks.

The next stage of the research involves analysing tens of thousands of patient images.

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Peter Dinham

Peter Dinham is a co-founder of iTWire and a 35-year veteran journalist and corporate communications consultant. He has worked as a journalist in all forms of media – newspapers/magazines, radio, television, press agency and now, online – including with the Canberra Times, The Examiner (Tasmania), the ABC and AAP-Reuters. As a freelance journalist he also had articles published in Australian and overseas magazines. He worked in the corporate communications/public relations sector, in-house with an airline, and as a senior executive in Australia of the world’s largest communications consultancy, Burson-Marsteller. He also ran his own communications consultancy and was a co-founder in Australia of the global photographic agency, the Image Bank (now Getty Images).

 

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