Surgical data science and artificial intelligence for surgical education
- PMID: 34245578
- DOI: 10.1002/jso.26496
Surgical data science and artificial intelligence for surgical education
Abstract
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.
Keywords: artificial intelligence; computer vision systems; data science; deep learning; surgical education.
© 2021 Wiley Periodicals LLC.
References
REFERENCES
-
- Maier-Hein L, Vedula SS, Speidel S, et al. Surgical data science for next-generation interventions. Nat Biomed Eng. 2017;1:691-696.
-
- Nagendran M, Chen Y, Lovejoy CA, et al. Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies. BMJ. 2020;368:m689.
-
- Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25:44-56.
-
- Hashimoto DA, Rosman G, Rus D, Meireles OR. Artificial Intelligence in Surgery: Promises and Perils. Ann Surg. 2018;268:70-76.
-
- Navarrete-Welton AJ, Hashimoto DA. Current applications of artificial intelligence for intraoperative decision support in surgery. Front Med. 2020;14:369-381.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Research Materials