Google AI looks at your eyes to predict heart disease risk

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For the study, the scientists developed deep learning models using retinal fundus images of almost 3, 00,000 people available from two countries; the United Kingdom and the U.S. and validated them using those from another 13,000 patients.

Expanding its horizons in the medical field, Google's new Artificial Intelligence (AI) algorithm is now able to detect diseases in human heart by merely looking in the eye. This unique method involves analyzing blood vessels in an area of the eye called the retinal fundus. The report states: "Most cardiovascular risk calculators use some combination of these parameters to identify patients at risk of experiencing either a major cardiovascular event or cardiac-related mortality within a pre-specified time period, such as ten years".

Deep-learning networks have already been used before to come up with algorithms that are able to diagnose diseases such as melanoma and blindness resulting from diabetes. Google's AI was checked for accuracy against two independently collected data sets, consisting of eye imagery from 12,026 and 999 patients.

Technology has not stopped unbelievable us and so has not Google. In other words, it's not yet ready for clinical testing, but it's a promising start for non-invasive evaluation of cardiovascular health.


Researchers from Google discovered a deep learning algorithm that can accurately predict cardiovascular risk factors based on images of a patient's eyes, according to a Monday Google Research Blog post.

As the paper points out, there are other ways of assessing cardiovascular risk from a patient's history and blood samples, but sometimes key information is missing, such as cholesterol levels. Explaining how the algorithm is making its prediction gives doctor more confidence in the algorithm itself.

"To make this useful for patients, we will be seeking to understand the effects of interventions such as lifestyle changes or medications on our risk predictions and we will be generating new hypotheses and theories to test", Peng said. This could help scientists generate more targeted hypotheses and drive a wide range of future research. "However, we don't precisely know in a particular individual how these factors add up, so in some patients, we may perform sophisticated tests ... to help better stratify an individual's risk for having a cardiovascular event such as a heart attack or stroke", declared study co-author Dr. Michael McConnell, a medical researcher at Verily.

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