Google AI device could predict a person's risk of a heart attack

Google Scientists Create Algorithm For Heart Attack Risk Based On Retinal Scans

Google's new AI algorithm predicts heart disease by looking at your eyes

In case you're wondering why Google and Verily chose retinal imaging for this breakthrough medical advancement, the rear interior wall of an eye called the fundus is jammed with blood vessels that reflect the body's overall health. 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".

In a study published on Monday in the journal Nature Biomedical Engineering, Google AI researchers described how deep learning algorithms can be trained to predict heart disease symptoms by looking at retinal images. This information included eye scans as well as general medical data. In the testing phases, the algorithm was able to identify heart conditions 70% of the time, which is a slightly lower rate of success than the longer SCORE process which is correct around 72% of the time. More research would resolve whether the model needs to be adjusted for larger or smaller photos, and a larger data set than what the researchers used is more appropriate for deep learning. "They're taking data that's been captured for one clinical reason and getting more out of it than we now do", said Oakden-Rayner. Discovering that we could do this is a good first step. While the link between the eyes and the heart may be somewhat well-known, no human could ever hope to study enough pairs of peepers to actually figure out what all of the different properties of the eye meant as far as heart disease risk. By studying their appearance with camera and microscope, doctors can infer things like an individual's blood pressure, age, and whether or not they smoke, all of which are crucial indicators of cardiovascular health. These techniques allow us to generate a heatmap that shows which pixels were the most important for a predicting a specific CV risk factor.

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Verily trained these models using data from almost 300,000 patients, with the system then associating these factors together. Google just combined that reality with technology to take the diagnostic potential to another level. In the future, doctors will be able to screen for the number one killer worldwide much more easily, and they will be doing it without causing us any physical discomfort. DeepMind, the London-based AI-development firm bought by Google in 2014 that often operates autonomously, released research earlier this month showing similar algorithms could help detect signs of glaucoma and other eye diseases.

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