Deep learning technology based on retinal scans was shown to be a good indicator of cardiovascular health and a predictor of potential heart attacks, and supremely accurate at indicating diabetes with the addition of expert assessment.
The most-quoted example of this was the University of Nottingham’s study last year, which developed a deep- and machine-learning algorithm to predict premature death in patients aged 40 to 69.
Based on health data from 2006 to 2010 from over half a million people within the age range, the deep learning program was “significantly more accurate in predicting death than the standard prediction models developed by a human expert.”
What this means in numbers is that the two AI algorithms were able to accurately identify 76% and 64% of subjects who died, respectively, while the human-generated prediction model predicted only 44%.
While the human model leaned heavily on the ethnicity, gender, age, and physical activity of the subjects, one algorithm focused on factors like body fat percentage and fruit and vegetable intake, while the most accurate algorithm looked mostly at job-related hazards and the consumption of alcohol and medication.
Progressing to its logical conclusion, AI systems will likely soon can accurately predict the life expectancy of anyone.