Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Apr 26, 2022; 10(12): 3729-3738
Published online Apr 26, 2022. doi: 10.12998/wjcc.v10.i12.3729
Flap failure prediction in microvascular tissue reconstruction using machine learning algorithms
Yu-Cang Shi, Jie Li, Shao-Jie Li, Zhan-Peng Li, Hui-Jun Zhang, Ze-Yong Wu, Zhi-Yuan Wu
Yu-Cang Shi, Jie Li, Shao-Jie Li, Zhan-Peng Li, Hui-Jun Zhang, Ze-Yong Wu, Zhi-Yuan Wu, Department of Plastic Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, Guangdong Province, China
Author contributions: Shi YC and Li J contributed equally to this work; Shi YC and Li J were responsible for conceptualization, data curation, and methodology and wrote the original draft; Li SJ, Li ZP and Zhang HJ analyzed the data and edited the manuscript; Wu ZY was responsible for validation and supervision and reviewed the manuscript; All authors approved the final submission.
Institutional review board statement: This study was approved by the Ethics Committee of the Affiliated Hospital of Guangdong Medical University.
Informed consent statement: The data used in this study were not involved in the patients’ privacy information, so the informed consent was waived by the Ethics Committee of the Affiliated Hospital of Guangdong Medical University.
Conflict-of-interest statement: The authors have no conflicts of interest to declare.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Zhi-Yuan Wu, MD, PhD, Professor, Department of Plastic Surgery, Affiliated Hospital of Guangdong Medical University, No. 57 South of Renmin Avenue, Zhanjiang 524001, Guangdong Province, China. 1608700812@qq.com
Received: December 14, 2021
Peer-review started: December 14, 2021
First decision: January 26, 2022
Revised: February 11, 2022
Accepted: March 6, 2022
Article in press: March 6, 2022
Published online: April 26, 2022
Processing time: 128 Days and 3.1 Hours
Core Tip

Core Tip: Flap failure is a rare but severe event in microvascular tissue reconstruction. It is generally associated with the additional economic burden and mental stress to the patients. Therefore, identifying the risk factors and screening high-risk patients carries a significant value in the clinical practice. Machine learning is an artificial intelligence based on the computer learning to learn from data and thus automatically make decisions. This retrospective study applied machine learning for the risk factor analysis of flap failure during microvascular tissue reconstruction.