Re-timing mortality risk through individualized modelling of lifespan trajectories nature.com

Researchers led by Ting Xu and Ching-Yu Cheng at the National University of Singapore developed RetiME, a deep-learning tool that estimates mortality risk from retinal photographs. Trained on a European cohort and tested in three independent cohorts across Southeast Asia, Eurasia and North America, it was associated with all-cause and cause-specific deaths and generated lifespan-risk trajectories showing distinct cancer, cardiometabolic and neurodegenerative patterns.