Google and its science department have some great news. The company’s health-tech subsidiary Verily is working on a new way to estimate the risks associated with heart disease – by using machine learning. Data collected from people’s retina scans has been analyzed and put through proprietary software that can apparently predict a major cardiac event — such as a heart attack — with roughly the same accuracy as current leading techniques.
The AI can accurately deduce this through data, including an individual’s age, blood pressure, and whether or not they smoke.
According to the company, medical researchers have previously shown some correlation between retinal vessels and the risk of a major cardiovascular episode. Using the retinal image, Google says it was able to quantify this association and 70% of the time accurately predict which patient within five years would experience a heart attack or other major cardiovascular event, and which patient would not.
A paper on their findings has been published today in the Nature journal Biomedical Engineering, although the research was also shared before peer review last September.
Alun Hughes, professor of Cardiovascular Physiology and Pharmacology at London’s UCL, said Google’s approach sounded credible because of the “long history of looking at the retina to predict cardiovascular risk.” He added that artificial intelligence had the potential to speed up existing forms of medical analysis, but cautioned that the algorithm would need to be tested further before it could be trusted.
Experts still don’t think it will be necessary for Google’s technology to replace conventional, human-powered care in the near future.
While most medical algorithms are built to replicate existing diagnostic tools (like identifying skin cancer, for example), this algorithm found new ways to analyze existing medical data. With enough data, it’s hoped that artificial intelligence can then create entirely new medical insight without human direction. It’s presumably part of the reason Google has created initiatives like its Project Baseline study, which is collecting exhaustive medical records of 10,000 individuals over the course of four years.
To train the algorithm, Google and Verily’s scientists used machine learning to analyze a medical dataset of nearly 300,000 patients.