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深度学习与生成式人工智能在衰老研究和健康长寿医学中的应用

Deep learning and generative artificial intelligence in aging research and healthy longevity medicine.

作者信息

Wilczok Dominika

机构信息

Duke University, Durham, NC 27708, USA.

Duke Kunshan University, Kunshan, Jiangsu 215316, China.

出版信息

Aging (Albany NY). 2025 Jan 16;17(1):251-275. doi: 10.18632/aging.206190.

DOI:10.18632/aging.206190
PMID:39836094
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11810058/
Abstract

With the global population aging at an unprecedented rate, there is a need to extend healthy productive life span. This review examines how Deep Learning (DL) and Generative Artificial Intelligence (GenAI) are used in biomarker discovery, deep aging clock development, geroprotector identification and generation of dual-purpose therapeutics targeting aging and disease. The paper explores the emergence of multimodal, multitasking research systems highlighting promising future directions for GenAI in human and animal aging research, as well as clinical application in healthy longevity medicine.

摘要

随着全球人口以前所未有的速度老龄化,有必要延长健康的生产寿命。本综述探讨了深度学习(DL)和生成式人工智能(GenAI)如何用于生物标志物发现、深度衰老时钟开发、老年保护剂鉴定以及针对衰老和疾病的两用疗法的生成。本文探讨了多模态、多任务研究系统的出现,突出了GenAI在人类和动物衰老研究以及健康长寿医学临床应用方面有前景的未来方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/d71bbbb8abe6/aging-17-206190-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/5f5d1abb031a/aging-17-206190-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/be1fc58f7ecc/aging-17-206190-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/b4628adae597/aging-17-206190-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/d71bbbb8abe6/aging-17-206190-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/5f5d1abb031a/aging-17-206190-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/be1fc58f7ecc/aging-17-206190-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/b4628adae597/aging-17-206190-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a915/11810058/d71bbbb8abe6/aging-17-206190-g004.jpg

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