Insilico Medicine, Hong Kong Science and Technology Park, Hong Kong, China; The Buck Institute for Research on Aging, Novato, CA, USA; The Biogerontology Research Foundation, London, UK.
Insilico Medicine, Hong Kong Science and Technology Park, Hong Kong, China; Computer Science Department, University of Oxford, Oxford, UK.
Trends Pharmacol Sci. 2019 Aug;40(8):546-549. doi: 10.1016/j.tips.2019.05.004. Epub 2019 Jul 3.
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).
深度学习（DL）预测法于 2016 年首次发表，目前在衰老研究领域迅速流行。这些深度衰老时钟可广泛应用于制药行业，涵盖目标识别、药物发现、数据经济和合成患者数据生成。在此，我们简要概述了使用人工智能（AI）开发的这一重要子集或超集的衰老时钟的最新进展。
