XAI is a rapidly progressing field of machine learning, aiming to unravel the predictions of
complex models. XAI is especially required in sensitive applications, eg in health care, when …

Background An individual's biological age is a measurement of health status and provides a
mechanistic understanding of aging. Age clocks estimate a biological age of an individual …

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 …

Background Biological age is a measure of health that offers insights into ageing. The
existing age clocks, although valuable, often trade off accuracy and interpretability. We …

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

The development of 'age clocks', machine learning models predicting age from biological
data, has been a major milestone in the search for reliable markers of biological age and …

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 …

The development of anti-aging interventions requires quantitative measurement of biological
age. Machine learning models, known as “aging clocks,” are built by leveraging diverse …

Attaining personalized healthy aging requires accurate monitoring of physiological changes
and identifying subclinical markers that predict accelerated or delayed aging. Classic …

Recent advances in deep learning enabled the development of AI systems that outperform
humans in many tasks and have started to empower scientists and physicians with new …