AI Uncovers the Biomarkers That Are Related to Aging

A bioinformatics company called Insilico Medicine has just announced Aging.AI, an online platform that guesses a person's age using data from blood tests. In the study to be published in Aging, the researchers designed a modular ensemble of 21 deep neural networks (DNNs) of varying depth and structure to predict age using a basic blood test. This ensemble was able to determine an individual's age around 80% of the time. The study also determined the five most important markers for predicting human chronological age: albumin, glucose, alkaline phosphatase, urea, and erythrocytes. Determining these biomarkers is important, since one of the major impediments in aging research is the absence of a set of biomarkers that may be measured to track the effectiveness of therapies.