Publication Name	World Journal of Gastrointestinal Surgery
Manuscript ID	106340
Country	China

Received	2025-02-24 13:47
Peer-Review Started	2025-02-24 13:47
To Make the First Decision
Return for Revision	2025-03-11 07:48
Revised	2025-03-13 04:35
Second Decision	2025-03-19 02:38
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-03-19 07:49
Articles in Press	2025-03-19 07:49
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2025-03-30 15:44
Publish the Manuscript Online	2025-07-23 11:10

ISSN	1948-9366 (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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Category	Gastroenterology & Hepatology
Manuscript Type	Editorial
Article Title	Application and challenges of artificial intelligence in predicting perioperative complications of colorectal cancer
Manuscript Source	Invited Manuscript
All Author List	Yang-Yang Fu, Yan Jiao, Ya-Hui Liu and Shan-Shan Dong
ORCID	Author(s) ORCID Number Yan Jiao http://orcid.org/0000-0001-6914-7949 Ya-Hui Liu http://orcid.org/0000-0003-3081-8156
Funding Agency and Grant Number
Corresponding Author	Ya-Hui Liu, Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, The First Hospital of Jilin University, No. 1 Xinmin Street, Changchun 130021, Jilin Province, China. yahui@jlu.edu.cn
Key Words	Artificial intelligence; Colorectal cancer; Perioperative complications; Machine learning; Predictive models
Core Tip	Artificial intelligence (AI), including machine learning and deep learning, is increasingly applied to predict perioperative complications in colorectal cancer surgery. By analyzing diverse data sources such as electronic health records, medical imaging, and preoperative markers, AI models can improve risk stratification, predict complications like anastomotic leakage and mortality, and enhance clinical decision-making. However, challenges such as data quality, model generalizability, and ethical concerns must be addressed. Future efforts should focus on developing interpretable models, utilizing multicenter datasets, and integrating AI into clinical workflows to optimize patient outcomes and ensure successful clinical adoption.
Publish Date	2025-07-23 11:10
Citation	<p>Fu YY, Jiao Y, Liu YH, Dong SS. Application and challenges of artificial intelligence in predicting perioperative complications of colorectal cancer. <i>World J Gastrointest Surg</i> 2025; 17(7): 106340</p>
URL	https://www.wjgnet.com/1948-9366/full/v17/i7/106340.htm
DOI	https://dx.doi.org/10.4240/wjgs.v17.i7.106340

Full Article (PDF)	WJGS-17-106340-with-cover.pdf
Manuscript File	106340_Auto_Edited_075636.docx
Answering Reviewers	106340-answering-reviewers.pdf
Audio Core Tip	106340-audio.mp3
Conflict-of-Interest Disclosure Form	106340-conflict-of-interest-statement.pdf
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Non-Native Speakers of English Editing Certificate	106340-non-native-speakers.pdf
Peer-review Report	106340-peer-reviews.pdf
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Scientific Editor Work List	106340-scientific-editor-work-list.pdf
CrossCheck Report	106340-crosscheck-report.pdf