Publication Name	World Journal of Gastrointestinal Surgery
Manuscript ID	88203
Country	China

Received	2023-09-14 12:07
Peer-Review Started	2023-09-14 12:09
To Make the First Decision
Return for Revision	2023-11-17 09:12
Revised	2023-11-24 12:12
Second Decision	2023-12-21 02:38
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2023-12-21 05:58
Articles in Press	2023-12-21 05:58
Publication Fee Transferred
Edit the Manuscript by Language Editor	2023-12-20 02:53
Typeset the Manuscript	2024-01-19 02:46
Publish the Manuscript Online	2024-01-25 06:43

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	Retrospective Study
Article Title	Predictive value of machine learning models for lymph node metastasis in gastric cancer: A two-center study
Manuscript Source	Unsolicited Manuscript
All Author List	Tong Lu, Miao Lu, Dong Wu, Yuan-Yuan Ding, Hao-Nan Liu, Tao-Tao Li and Da-Qing Song
ORCID	Author(s) ORCID Number Tong Lu http://orcid.org/0000-0002-7674-2065 Da-Qing Song http://orcid.org/0009-0001-5677-1598
Funding Agency and Grant Number
Corresponding Author	Da-Qing Song, Doctor, Additional Professor, Department of Emergency Medicine, Jining No.1 People's Hospital , No. 6 Jiankang Road, Rencheng District, Jining 272000, Shandong Province, China. 19552153365@163.com
Key Words	Machine learning; Prediction model; Gastric cancer; Lymph node metastasis
Core Tip	The purpose of this study was to explore the performance of a clinical model built by machine learning (ML) for the risk assessment of lymph node metastasis in patients with gastric cancer. We used 7 different ML methods to analyze our date,After training, the algorithm with the highest average area under the receiver operating characteristic curve is selected as the optimal algorithm.
Publish Date	2024-01-25 06:43
Citation	Lu T, Lu M, Wu D, Ding YY, Liu HN, Li TT, Song DQ. Predictive value of machine learning models for lymph node metastasis in gastric cancer: A two-center study. World J Gastrointest Surg 2024; 16(1): 85-94
URL	https://www.wjgnet.com/1948-9366/full/v16/i1/85.htm
DOI	https://dx.doi.org/10.4240/wjgs.v16.i1.85

Full Article (PDF)	WJGS-16-85-with-cover.pdf
Full Article (Word)	WJGS-16-85.docx
Manuscript File	88203_Auto_Edited-XLQ-WangTQ-YJP.docx
Answering Reviewers	88203-Answering reviewers.pdf
Audio Core Tip	88203-Audio core tip.mp3
Biostatistics Review Certificate	88203-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form	88203-Conflict-of-interest statement.pdf
Copyright License Agreement	88203-Copyright license agreement.pdf
Signed Informed Consent Form(s) or Document(s)	88203-Informed consent statement.pdf
Institutional Review Board Approval Form or Document	88203-Institutional review board statement.pdf
Non-Native Speakers of English Editing Certificate	88203-Language certificate.pdf
Peer-review Report	88203-Peer-review(s).pdf
Scientific Misconduct Check	88203-Bing-Qu XL-2.jpg
Scientific Editor Work List	88203-Scientific editor work list.pdf
CrossCheck Report	88203-CrossCheck report.pdf