Google has developed a new artificial intelligence (AI) robot that can predict a patient’s risk of heart disease and other cardiovascular events.
The new robot, built in partnership with health organisation Verily, uses AI to analyse data from almost 300,000 patients and then predict cardiovascular outcomes based on the data and patient assessment.
Deep learning is used to spot patterns in the information, learning the early signs of life threatening diseases from eye scans and the metrics needed to predict the risk.
The tech giant’s new robot reads a patient’s retinas to assess the risk of heart disease. The machine scans the back of a patient’s eye and can then predict risk factors such as age, blood pressure and whether or not a patient smokes.
All the data is the collated together, which the robot uses to analyse and predict the risk of suffering a life-threatening cardiac event such as a heart attack. The technology is beneficial to both patients and healthcare workers, firstly because of its ease of assessment and capabilities. Secondly, it is a much less invasive procedure than a routine blood test.
The robot is as accurate as doctors.
Google has said that the technology is just as accurate as results from Doctors would be. In a research blog post the tech giant said: “Using deep learning algorithms trained on data from 284,335 patients, we were able to predict CV risk factors from retinal images with surprisingly high accuracy for patients from two independent datasets of 12,026 and 999 patients. Our algorithm could distinguish the retinal images of a smoker from that of a non-smoker 71% of the time.”
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The Silicon Valley company said that the AI robot was also ‘fairly accurate’ at predicting the risk of a cardiovascular event directly, using the image to quantify the image and risk of heart attack or stroke. An accuracy level of 70% was recorded by Google when the technology predicted whether a patient would suffer a cardiac event in the next five years.
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Google’s aim is to make predictions for life threatening diseases much more accurate, as well as ensuring patients are assessed in the least invasive and most effective way.
The tech giant said: “At the broadest level, we are excited about this work because it may represent a new method of scientific discovery. We look forward to developing and testing our algorithm on larger and more comprehensive datasets.”
