Biological age is a universal marker of aging, stress, and frailty

• Published in: bioRxiv
• Main Authors: Pyrkov, Timothy V, Fedichev, Peter O
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 14.03.2019
• Subjects: Age; Aging; C-reactive protein; Mental disorders; Morbidity; Neural networks; Quality of life; Smoking; Survival

We carried out a systematic investigation of supervised learning techniques for biological age modeling. The biological aging acceleration is associated with the remaining health- and life-span. Artificial Deep Neural Networks (DNN) could be used to reduce the error of chronological age predictors,...