Leveraging physiology and artificial intelligence to deliver advancements in health care

被引:11
|
作者
Zhang, Angela [1 ,2 ,3 ]
Wu, Zhenqin [4 ]
Wu, Eric [5 ]
Wu, Matthew [3 ]
Snyder, Michael P. P. [2 ]
Zou, James [6 ,7 ]
Wu, Joseph C. C. [1 ,3 ,8 ,9 ]
机构
[1] Stanford Univ, Stanford Cardiovasc Inst, Sch Med, Stanford, CA 94305 USA
[2] Stanford Univ, Sch Med, Dept Genet, Stanford, CA 94305 USA
[3] Greenstone Biosci, Palo Alto, CA 94304 USA
[4] Stanford Univ, Dept Chem, Stanford, CA USA
[5] Stanford Univ, Dept Elect Engn, Stanford, CA USA
[6] Stanford Univ, Sch Med, Dept Biomed Informat, Stanford, CA USA
[7] Stanford Univ, Dept Comp Sci, Stanford, CA USA
[8] Stanford Univ, Dept Med, Div Cardiovasc Med, Stanford, CA USA
[9] Stanford Univ, Sch Med, Dept Radiol, Stanford, CA USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
artificial intelligence; health care; medicine; physiology; DEEP-LEARNING ALGORITHM; DIABETIC-RETINOPATHY; PREDICTIVE MODELS; IMAGE CLASSIFICATION; CLINICAL VALIDATION; WEARABLE TECHNOLOGY; SKIN-CANCER; RISK; AI; DERMATOLOGISTS;
D O I
10.1152/physrev.00033.2022
中图分类号
Q4 [生理学];
学科分类号
071003 ;
摘要
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 artifi- cial 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.
引用
收藏
页码:2423 / 2450
页数:29
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