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MINI REVIEW article

Front. Surg.
Sec. Visceral Surgery
Volume 11 - 2024 | doi: 10.3389/fsurg.2024.1493779
This article is part of the Research Topic Exploring Machine Learning Applications in Visceral Surgery View all 3 articles

Machine Learning Perioperative Applications in Visceral Surgery: A Narrative Review

Provisionally accepted
Intekhab Hossain Intekhab Hossain 1,2*Amin Madani Amin Madani 1,2Simon Laplante Simon Laplante 1,2
  • 1 Department of Surgery, University of Toronto, Toronto, Ontario, Canada
  • 2 Surgical Artiļ¬cial Intelligence Research Academy, Toronto, Canada

The final, formatted version of the article will be published soon.

    Artificial intelligence in surgery has seen an expansive rise in research and clinical implementation in recent years, with many of the models being driven by machine learning. In the preoperative setting, machine learning models have been utilized to guide indications for surgery, appropriate timing of operations, calculation of risks and prognostication, along with improving estimations of time and resources required for surgeries. Intraoperative applications that have been demonstrated are visual annotations of the surgical field, automated classification of surgical phases and prediction of intraoperative patient decompensation. Postoperative applications have been studied the most, with most efforts put towards prediction of postoperative complications, recurrence patterns of malignancy, enhanced surgical education and assessment of surgical skill. Challenges to implementation of these models in clinical practice include the need for more quantity and quality of standardized data to improve model performance, sufficient resources and infrastructure to train and use machine learning, along with addressing ethical and patient acceptance considerations.

    Keywords: machine learning (ML), Preoperative, intraoperative, postoperative, applications

    Received: 09 Sep 2024; Accepted: 18 Oct 2024.

    Copyright: Ā© 2024 Hossain, Madani and Laplante. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Intekhab Hossain, Department of Surgery, University of Toronto, Toronto, M5S 1A1, Ontario, Canada

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.