Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity.

Clicks: 310
ID: 2176
2019
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Ranked #3 of 39 articles by views in trends in pharmacological sciences

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Abstract
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 aging clocks can be used in a broad range of applications in the pharmaceutical industry, spanning target identification, drug discovery, data economics, and synthetic patient data generation. We provide here a brief overview of recent advances in this important subset, or perhaps superset, of aging clocks that have been developed using artificial intelligence (AI).
Reference Key
zhavoronkov2019deeptrends Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zhavoronkov, Alex;Mamoshina, Polina;
Journal trends in pharmacological sciences
Year 2019
DOI
S0165-6147(19)30114-2
URL
Keywords Keywords not found

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