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基于人工智能的方法来识别卓越健康和长寿的分子决定因素——美国国立衰老研究所的跨学科研讨会

Artificial Intelligence Based Approaches to Identify Molecular Determinants of Exceptional Health and Life Span-An Interdisciplinary Workshop at the National Institute on Aging.

作者信息

Moore Jason H, Raghavachari Nalini

机构信息

University of Pennsylvania, Philadelphia, PA, United States.

National Institute on Aging - NIH Bethesda, MD, United States.

出版信息

Front Artif Intell. 2019 Aug 6;2:12. doi: 10.3389/frai.2019.00012. eCollection 2019.

Abstract

Artificial intelligence (AI) has emerged as a powerful approach for integrated analysis of the rapidly growing volume of multi-omics data, including many research and clinical tasks such as prediction of disease risk and identification of potential therapeutic targets. However, the potential for AI to facilitate the identification of factors contributing to human exceptional health and life span and their translation into novel interventions for enhancing health and life span has not yet been realized. As researchers on aging acquire large scale data both in human cohorts and model organisms, emerging opportunities exist for the application of AI approaches to untangle the complex physiologic process(es) that modulate health and life span. It is expected that efficient and novel data mining tools that could unravel molecular mechanisms and causal pathways associated with exceptional health and life span could accelerate the discovery of novel therapeutics for healthy aging. Keeping this in mind, the National Institute on Aging (NIA) convened an interdisciplinary workshop titled "Contributions of Artificial Intelligence to Research on Determinants and Modulation of Health Span and Life Span" in August 2018. The workshop involved experts in the fields of aging, comparative biology, cardiology, cancer, and computational science/AI who brainstormed ideas on how AI can be leveraged for the analyses of large-scale data sets from human epidemiological studies and animal/model organisms to close the current knowledge gaps in processes that drive exceptional life and health span. This report summarizes the discussions and recommendations from the workshop on future application of AI approaches to advance our understanding of human health and life span.

摘要

人工智能(AI)已成为一种强大的方法,用于对快速增长的多组学数据进行综合分析,包括许多研究和临床任务,如疾病风险预测和潜在治疗靶点的识别。然而,人工智能在促进识别有助于人类超常健康和寿命的因素并将其转化为增强健康和寿命的新干预措施方面的潜力尚未实现。随着衰老研究人员在人类队列和模式生物中获取大规模数据,应用人工智能方法来理清调节健康和寿命的复杂生理过程存在新的机会。预计能够揭示与超常健康和寿命相关的分子机制和因果途径的高效新颖数据挖掘工具,可以加速发现促进健康衰老的新疗法。牢记这一点,美国国立衰老研究所(NIA)于2018年8月召开了一次跨学科研讨会,题为“人工智能对健康寿命和寿命的决定因素及调节研究的贡献”。该研讨会邀请了衰老、比较生物学、心脏病学、癌症以及计算科学/人工智能领域的专家,他们就如何利用人工智能分析来自人类流行病学研究和动物/模式生物的大规模数据集以填补当前在驱动超常生命和健康寿命过程中的知识空白展开了头脑风暴。本报告总结了研讨会上关于人工智能方法未来应用的讨论和建议,以增进我们对人类健康和寿命的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14c4/7861312/899815cf89f5/frai-02-00012-g0001.jpg

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