Machine learning can be used to recognize faces, drive cars, and even
To develop its retina-scanning neural network, Google needed a lot of data. It used retinal images from 284,335 patients to set up the network. Later, it validated the network’s deep learning abilities using two different data sets of 12,026 and 999 patients. This was an important step as it showed that Google’s model could accurately predict health metrics. Just from retinal images, the model can determine age within about 3 years, gender (97 percent accuracy), smoking status (71 percent accuracy), blood pressure (within 11.23mmHg), and how likely it is that someone will have an “adverse cardiac event.” The model was able to predict that last one with 70 percent accuracy. It’s not a sure thing, but that’s pretty accurate when you consider it’s just looking at blood vessels in the eye.
The study is still just in preprint right now and has not been peer reviewed. Other researchers will need to go over the models and validate the results before we’ll know the impact, but it could be a boon to medicine. Even if it’s not 100 percent accurate, a retina scan is a simple, noninvasive procedure that could provide more data to doctors.
Published at Fri, 05 Jan 2018 15:45:49 +0000