Artificial intelligence in surgery

被引:22
|
作者
Varghese, Chris [1 ]
Harrison, Ewen M. [2 ]
O'Grady, Greg [1 ,3 ]
Topol, Eric J. [4 ]
机构
[1] Univ Auckland, Dept Surg, Auckland, New Zealand
[2] Univ Edinburgh, Usher Inst, Ctr Med Informat, Edinburgh, Scotland
[3] Univ Auckland, Auckland Bioengn Inst, Auckland, New Zealand
[4] Scripps Res Translat Inst, La Jolla, CA 92037 USA
基金
美国国家卫生研究院;
关键词
QUALITY-OF-LIFE; GENERALIZED ANXIETY DISORDER; LUNG-CANCER PATIENTS; PSYCHOLOGICAL DISTRESS; PLUS CHEMOTHERAPY; RISK-FACTORS; DEPRESSION; STRESS; PEMBROLIZUMAB; PREVALENCE;
D O I
10.1038/s41591-024-02970-3
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
Artificial intelligence (AI) is rapidly emerging in healthcare, yet applications in surgery remain relatively nascent. Here we review the integration of AI in the field of surgery, centering our discussion on multifaceted improvements in surgical care in the preoperative, intraoperative and postoperative space. The emergence of foundation model architectures, wearable technologies and improving surgical data infrastructures is enabling rapid advances in AI interventions and utility. We discuss how maturing AI methods hold the potential to improve patient outcomes, facilitate surgical education and optimize surgical care. We review the current applications of deep learning approaches and outline a vision for future advances through multimodal foundation models. This Review outlines the state of the art of artificial intelligence in the preoperative, intraoperative and postoperative settings, where it has enormous potential to improve patient outcomes, surgical education and system efficiencies.
引用
收藏
页码:1257 / 1268
页数:25
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