Feb 21, 2017

IBM’s Watson focuses on eye-care advances

IBM is putting the prowess of its cognitive computing champion Watson to further use in the healthcare space, with the tech giant shedding new light on the role it can play in the treatment of eye disease.
The research, which began in 2015, involved the US heavyweight’s Melbourne-based team of researchers training Watson to recognise irregularities in eye images, which in turn offers doctors greater confidence in the early identification of patients at risk of diabetic retinopathy and glaucoma.
The technology is applied to a dataset of 88,000 retina images to analyse the key anatomies of the eye. The granular examination of each image brings to light details that may often be missed by doctors. One example of Watson’s ability is the accuracy with which it measures the separation of the optic cup and disc, a symptom of increased eye pressure, with statistical performance as high as 95 per cent.
The technology has also been trained to distinguish between left and right eye images (with up to 94 per cent accuracy), which is important for downstream analysis and effective treatment programs.
IBM Research Australia vice-president and lab director Joann Batstone said medical images were a rich source of data, which was finally being tapped comprehensively and helping medical professionals diagnose illnesses “earlier and with greater confidence”.
“We are really focused on the early detection phase but diagnosis is just one piece of the overall outcome,” Dr Batstone told The Australian.
“The transformation opportunity is actually around our ability to track and measure the progression of disease by analysing multiple images over time. It paves the way for technology to become a clinician’s assistant.”
The work done by Dr Batstone and her team isn’t the first time Watson’s ability to absorb and analyse vast quantities of data has been put to the test in a medical context. IBM is already working with Melanoma Institute Australia to help further advance the identification of melanoma using Watson and has a research agreement with Molemap, which uses advanced visual analytics to pore over more than 40,000 data sets including images and text.
Its early days but the use of Watson provides a glimpse of the impact technologies such as machine learning and Artificial Intelligence are starting to make in healthcare. ASX-listed Volpara Health Technologies’s founding director, Professor Sir John Michael Brady, a pioneer in AI and professor of Oncological Imaging at the University of Oxford, said the advancements in software was pushing the boundaries of what AI could do.
Volpara’s technology does not work quite the same way as Watson. The company’s software analyses breast density to optimise the efficacy of breast cancer screening programs and, according to Professor Brady, provides an ideal path to diagnosis.
“Error of omission is the biggest impediment to early diagnosis because it’s impossible for doctors to be on top of everything,” he said. “In that context the best way forward is to make the systems smarter.”
He said the next step for smart technologies would be to make waves in the field of cancer treatment called Radiomics — where algorithms are used to extract large amount of quantitative features from medical images — and Theranostics, which is the application of molecular imaging and genetic information of a patient to develop a personalised treatment.
Both Dr Batstone and Professor Brady are also quick to dismiss talk of AI eventually rendering clinicians obsolete.




According to Dr Batstone, getting more value out of existing resources is likely to be the main focus.

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