A team of biomedical researchers has developed a non-invasive, more accurate, and inexpensive “aging clock” for tracking and slowing human aging by examining retinal images and using trained deep-learning models of the eye’s fundus (the deepest area of the eye), using a new “eyeAge” system. The researchers are affiliated with Buck Institute for Research on … Continue reading Deep-learning aging clock tracks human aging, detects eye and other diseases from retinal images