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eXplainable Artificial Intelligence (XAI) in aging clock models

delete2024-01-01
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OA
AI
A
Alena Kalyakulina *
I
Igor Yusipov
A
Alexey Moskalev
C
Claudio Franceschi
M
Mikhail Ivanchenko
DOI:10.1016/j.arr.2023.102144delete
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摘要

摘要

En 中文
XAI is a rapidly progressing field of machine learning, aiming to unravel the predictions of complex models. XAI is especially required in sensitive applications, e.g. in health care, when diagnosis, recommendations and treatment choices might rely on the decisions made by artificial intelligence systems. AI approaches have become widely used in aging research as well, in particular, in developing biological clock models and identifying biomarkers of aging and age-related diseases. However, the potential of XAI here awaits to be fully appreciated. We discuss the application of XAI for developing the aging clocks and present a comprehensive analysis of the literature categorized by the focus on particular physiological systems.
Keyword:
Explainable artificial intelligence
Aging
Longevity
Age-related diseases
Machine learning
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Ageing Research Reviews 封面图
Ageing Research Reviews
IF:
12.4
论文数:
3.6K
被引数:
2.3W

机构

L
Lobachevsky State University of Nizhni Novgorod
学者数:
2.3K
论文数: 1.2K
被引数: 2
R
russian academy of sciences
学者数:
9.1W
论文数: 6.0W
被引数: 60
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