Surgical data science and artificial intelligence for surgical education

被引：57

作者：

Ward, Thomas M. ^{[1
]}

Mascagni, Pietro ^{[2
,3
,4
]}

Madani, Amin ^{[5
]}

Padoy, Nicolas ^{[2
,4
]}

Perretta, Silvana ^{[4
,6
]}

Hashimoto, Daniel A. ^{[1
]}

机构：

[1] Massachusetts Gen Hosp, Dept Surg, Surg AI & Innovat Lab, 15 Parkman St,WAC460, Boston, MA 02114 USA

[2] Univ Strasbourg, ICube, CNRS, Strasbourg, France

[3] Fdn Policlin A Gemelli IRCCS, Rome, Italy

[4] IHU Strasbourg, Strasbourg, France

[5] Univ Hlth Network, Dept Surg, Toronto, ON, Canada

[6] IRCAD, Strasbourg, France

来源：

JOURNAL OF SURGICAL ONCOLOGY | 2021年 / 124卷 / 02期

关键词：

artificial intelligence; computer vision systems; data science; deep learning; surgical education; ADVERSE EVENTS; CRITICAL-VIEW; RECOGNITION; SAFETY; CHOLECYSTECTOMY; COMPETENCES; PREVENTION;

D O I：

10.1002/jso.26496

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Surgical data science (SDS) aims to improve the quality of interventional healthcare and its value through the capture, organization, analysis, and modeling of procedural data. As data capture has increased and artificial intelligence (AI) has advanced, SDS can help to unlock augmented and automated coaching, feedback, assessment, and decision support in surgery. We review major concepts in SDS and AI as applied to surgical education and surgical oncology.

引用

页码：221 / 230

页数：10

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