Executive summary of the artificial intelligence in surgery series

Tyler J. Loftus, Alexander P. J. Vlaar, Andrew J. Hung, Azra Bihorac, Bradley M. Dennis, Catherine Juillard, Daniel A. Hashimoto, Haytham M. A. Kaafarani, Patrick J. Tighe, Paul C. Kuo, Shuhei Miyashita, Steven D. Wexner, Kevin E. Behrns

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)

Abstract

As opportunities for artificial intelligence to augment surgical care expand, the accompanying surge in published literature has generated both substantial enthusiasm and grave concern regarding the safety and efficacy of artificial intelligence in surgery. For surgeons and surgical data scientists, it is increasingly important to understand the state-of-the-art, recognize knowledge and technology gaps, and critically evaluate the deluge of literature accordingly. This article summarizes the experiences and perspectives of a global, multi-disciplinary group of experts who have faced development and implementation challenges, overcome them, and produced incipient evidence thereof. Collectively, evidence suggests that artificial intelligence has the potential to augment surgeons via decision-support, technical skill assessment, and the semi-autonomous performance of tasks ranging from resource allocation to patching foregut defects. Most applications remain in preclinical phases. As technologies and their implementations improve and positive evidence accumulates, surgeons will face professional imperatives to lead the safe, effective clinical implementation of artificial intelligence in surgery. Substantial challenges remain; recent progress in using artificial intelligence to achieve performance advantages in surgery suggests that remaining challenges can and will be overcome.
Original languageEnglish
JournalSurgery (United States)
Early online date2021
DOIs
Publication statusE-pub ahead of print - 2021

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