AI in health and medicine

被引:1327
作者
Rajpurkar, Pranav [1 ]
Chen, Emma [2 ]
Banerjee, Oishi [2 ]
Topol, Eric J. [3 ]
机构
[1] Harvard Univ, Dept Biomed Informat, Cambridge, MA 02138 USA
[2] Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA
[3] Scripps Translat Sci Inst, San Diego, CA 92037 USA
基金
美国国家卫生研究院;
关键词
ARTIFICIAL-INTELLIGENCE; DIABETIC-RETINOPATHY; IMAGING DATA; DEEP; PREDICTION; SYSTEM; CANCER; CLASSIFICATION; PERFORMANCE; VALIDATION;
D O I
10.1038/s41591-021-01614-0
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
AI has the potential to reshape medicine and make healthcare more accurate, efficient and accessible; this Review discusses recent progress, opportunities and challenges toward achieving this goal. Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the experiences of both clinicians and patients. We discuss key findings from a 2-year weekly effort to track and share key developments in medical AI. We cover prospective studies and advances in medical image analysis, which have reduced the gap between research and deployment. We also address several promising avenues for novel medical AI research, including non-image data sources, unconventional problem formulations and human-AI collaboration. Finally, we consider serious technical and ethical challenges in issues spanning from data scarcity to racial bias. As these challenges are addressed, AI's potential may be realized, making healthcare more accurate, efficient and accessible for patients worldwide.
引用
收藏
页码:31 / 38
页数:8
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