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Publication Name World Journal of Gastroenterology
Manuscript ID 105283
Country China
Category Gastroenterology & Hepatology
Manuscript Type Retrospective Study
Article Title Interpretable machine learning model for anastomotic leakage after rectal cancer resection based on serum calcium: Multi-center study
Manuscript Source Unsolicited Manuscript
All Author List Bo-Yu Kang, Yi-Huan Qiao, Jun Zhu, Bao-Liang Hu, Ze-Cheng Zhang, Ji-Peng Li and Yan-Jiang Pei
Funding Agency and Grant Number
Funding Agency Grant Number
National Natural Science Foundation of China 82172781
Shaanxi Health Scientific Research Innovation Team Project 2024TD-06
Corresponding Author Yan-Jiang Pei, MD, PhD, Professor, Department of Digestive Surgery, Honghui Hospital, Xi'an Jiaotong University., No. 555, Youyi East Road, Beilin District, Xi’an City, Shaanxi Province, China,, Xi’an 710032, Shanxi Province, China. 15829329200@126.com
Key Words Machine learning; Rectal cancer; Anastomotic leakage; Shapley Additive exPlanations algorithms
Core Tip Ten machine learning models were established using 10 factors and interpreted using the Shapley Additive exPlanations model. Through model evaluation and comparison, we selected the best prediction model and performed external validation in multiple centers; We found for the first time that perioperative serum calcium ion level plays an important role in the occurrence of anastomotic leakage (AL) after anterior resection of rectal cancer, and proposed that preoperative serum calcium ion lower than 2.1 and postoperative calcium ion lower than 2.2 are clinical warning values for the occurrence of AL.
Citation Kang BY, Qiao YH, Zhu J, Hu BL, Zhang ZC, Li JP, Pei YJ. Interpretable machine learning model for anastomotic leakage after rectal cancer resection based on serum calcium: Multi-center study. World J Gastroenterol 2025; In press
Received
2025-01-17 15:47
Peer-Review Started
2025-01-17 15:47
To Make the First Decision
Return for Revision
2025-03-19 23:14
Revised
2025-03-27 10:21
Second Decision
2025-04-27 02:41
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief
2025-04-27 05:58
Articles in Press
2025-04-27 05:58
Publication Fee Transferred
2025-03-28 06:42
Edit the Manuscript by Language Editor
2025-04-28 03:31
Typeset the Manuscript
ISSN 1007-9327 (print) and 2219-2840 (online)
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/
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