An explainable AI framework for interpretable biological age
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 …
mechanistic understanding of aging. Age clocks estimate a biological age of an individual …
ExplaiNAble BioLogical Age (ENABL Age): an artificial intelligence framework for interpretable biological age
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 …
existing age clocks, although valuable, often trade off accuracy and interpretability. We …
eXplainable Artificial Intelligence (XAI) in age prediction: A systematic review
A Kalyakulina, I Yusipov - arXiv preprint arXiv:2307.13704, 2023 - arxiv.org
eXplainable Artificial Intelligence (XAI) is now an important and essential part of machine
learning, allowing to explain the predictions of complex models. XAI is especially required in …
learning, allowing to explain the predictions of complex models. XAI is especially required in …
eXplainable Artificial Intelligence (XAI) in aging clock models
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 …
complex models. XAI is especially required in sensitive applications, eg in health care, when …
Explainable machine learning framework to predict personalized physiological aging
Attaining personalized healthy aging requires accurate monitoring of physiological changes
and identifying subclinical markers that predict accelerated or delayed aging. Classic …
and identifying subclinical markers that predict accelerated or delayed aging. Classic …
Application of AI in biological age prediction
D Meng, S Zhang, Y Huang, K Mao, JDJ Han - Current Opinion in Structural …, 2024 - Elsevier
The development of anti-aging interventions requires quantitative measurement of biological
age. Machine learning models, known as “aging clocks,” are built by leveraging diverse …
age. Machine learning models, known as “aging clocks,” are built by leveraging diverse …
Assessing the rate of aging to monitor aging itself
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 …
can be quantified by biological aging rates estimated by aging clocks. Generation and …
[HTML][HTML] Deep aging clocks: the emergence of AI-based biomarkers of aging and longevity
A Zhavoronkov, P Mamoshina - Trends in Pharmacological Sciences, 2019 - cell.com
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 …
deep learning (DL) are rapidly gaining popularity in the aging research community. These …
ClockBase: a comprehensive platform for biological age profiling in human and mouse
Aging represents the greatest risk factor for chronic diseases and mortality, but to
understand it we need the ability to measure biological age. In recent years, many machine …
understand it we need the ability to measure biological age. In recent years, many machine …
An interpretable biological age
Q Zhang - The Lancet Healthy Longevity, 2023 - thelancet.com
Biological age as an integrated value of biophysiological measures has been widely
investigated as a biomarker of ageing. It outperforms chronological age in predicting the …
investigated as a biomarker of ageing. It outperforms chronological age in predicting the …