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REVIEW article

Front. Surg.

Sec. Colorectal and Proctological Surgery

Volume 12 - 2025 | doi: 10.3389/fsurg.2025.1551838

Artificial intelligence-assisted phase recognition and skill assessment in laparoscopic surgery: A systematic review

Provisionally accepted
Wenqiang Liao Wenqiang Liao 1Ying Zhu Ying Zhu 2Hanwei Zhang Hanwei Zhang 3Dan Wang Dan Wang 2Lijun Zhang Lijun Zhang 4Tianxiang Chen Tianxiang Chen 5Ru Zhou Ru Zhou 1Zi Ye Zi Ye 3*
  • 1 Department of Surgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
  • 2 Hangzhou Institute for Advanced Study, University of Chinese Academy of Science, Hangzhou, Jiangsu Province, China
  • 3 Institute of Intelligent Software, Guangzhou 511458, China, Guangzhou, China
  • 4 Institute of Software Chinese Academy of Sciences, 100190, Beijing, Beijing, China
  • 5 School of Cyber Space and Technology, University of Science and Technology of China, Hefei 230026, China, Hefei, China

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

    With the widespread adoption of minimally invasive surgery, laparoscopic surgery has been an essential component of modern surgical procedures. As key technologies, laparoscopic phase recognition and skill evaluation aim to identify different stages of the surgical process and assess surgeons' operational skills using automated methods. This, in turn, can improve the quality of surgery and the skill of surgeons. This review summarizes the progress of research in laparoscopic surgery, phase recognition, and skill evaluation. At first, the importance of laparoscopic surgery is introduced, clarifying the relationship between phase recognition, skill evaluation, and other surgical tasks. The publicly available surgical datasets for laparoscopic phase recognition tasks are then detailed. The review highlights the research methods that have exhibited superior performance in these public datasets and identifies common characteristics of these highperforming methods. Based on the insights obtained, the commonly used phase recognition research and surgical skill evaluation methods and models in this field are summarized. In addition, this study briefly outlines the standards and methods for evaluating laparoscopic surgical skills. Finally, an analysis of the difficulties researchers face and potential future development directions is presented. Moreover, this paper aims to provide valuable references for researchers, promoting further advancements in this domain.

    Keywords: laparoscopic surgery, Phase recognition, skill evaluation, methods, Surgical datasets

    Received: 26 Dec 2024; Accepted: 27 Mar 2025.

    Copyright: © 2025 Liao, Zhu, Zhang, Wang, Zhang, Chen, Zhou and Ye. 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: Zi Ye, Institute of Intelligent Software, Guangzhou 511458, China, Guangzhou, China

    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.

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