First published in 2016, predictors of chronological and biological age developed using
deep learning (DL) are rapidly gaining popularity in the aging research community. These …

Multiple recent advances in machine learning enabled computer systems to exceed human
performance in many tasks including voice, text, and speech recognition and complex …

Healthy aging is the prime goal of aging research and interventions. Healthy aging or not
can be quantified by biological aging rates estimated by aging clocks. Generation and …

Accurate and physiologically meaningful biomarkers for human aging are key to assessing
antiaging therapies. Given ethnic differences in health, diet, lifestyle, behavior …

Abstract Machine learning models capable of predicting age given a set of inputs are
referred to as aging clocks. We recently developed an aging clock that utilizes 491 plasma …

Aging is a significant contributor to various chronic diseases, thus emerging as an
increasingly important area of research. Elucidating the mechanisms underlying aging can …

The applications of modern artificial intelligence (AI) algorithms within the field of aging
research offer tremendous opportunities. Aging is an almost universal unifying feature …

Aging is emerging as a druggable target with growing interest from academia, industry and
investors. New technologies such as artificial intelligence and advanced screening …

While in the past technology has mostly been utilized to store information about the
structural configuration of proteins and molecules for research and medical purposes …

The aging process results in multiple traceable footprints, which can be quantified and used
to estimate an organism's age. Examples of such aging biomarkers include epigenetic …