Leveraging physiology and artificial intelligence to deliver advancements in health care.

IF 29.9 1区 医学 Q1 PHYSIOLOGY
Physiological reviews Pub Date : 2023-10-01 Epub Date: 2023-04-27 DOI:10.1152/physrev.00033.2022
Angela Zhang, Zhenqin Wu, Eric Wu, Matthew Wu, Michael P Snyder, James Zou, Joseph C Wu
{"title":"Leveraging physiology and artificial intelligence to deliver advancements in health care.","authors":"Angela Zhang, Zhenqin Wu, Eric Wu, Matthew Wu, Michael P Snyder, James Zou, Joseph C Wu","doi":"10.1152/physrev.00033.2022","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: automating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact.</p>","PeriodicalId":20193,"journal":{"name":"Physiological reviews","volume":null,"pages":null},"PeriodicalIF":29.9000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10390055/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physiological reviews","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1152/physrev.00033.2022","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/4/27 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PHYSIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: automating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact.

利用生理学和人工智能在医疗保健领域取得进步。
在过去的十年里,医疗保健领域的人工智能经历了显著的创新和进步。重大进展可归因于利用人工智能转换生理数据以促进医疗保健。在这篇综述中,我们探讨了过去的工作如何塑造了这个领域,并确定了未来的挑战和方向。我们特别关注三个发展领域。首先,我们概述了人工智能,特别关注最相关的人工智能模型。然后,我们详细介绍了人工智能如何利用生理学数据来推进医疗保健的主要领域:自动化现有的医疗保健任务,增加获得医疗保健的机会,以及增强医疗保健能力。最后,我们讨论了围绕个人生理学数据使用的新问题,并详细说明了该领域日益重要的考虑因素,即部署人工智能模型以实现有意义的临床影响的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Physiological reviews
Physiological reviews 医学-生理学
CiteScore
56.50
自引率
0.90%
发文量
53
期刊介绍: Physiological Reviews is a highly regarded journal that covers timely issues in physiological and biomedical sciences. It is targeted towards physiologists, neuroscientists, cell biologists, biophysicists, and clinicians with a special interest in pathophysiology. The journal has an ISSN of 0031-9333 for print and 1522-1210 for online versions. It has a unique publishing frequency where articles are published individually, but regular quarterly issues are also released in January, April, July, and October. The articles in this journal provide state-of-the-art and comprehensive coverage of various topics. They are valuable for teaching and research purposes as they offer interesting and clearly written updates on important new developments. Physiological Reviews holds a prominent position in the scientific community and consistently ranks as the most impactful journal in the field of physiology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信