Publication Name	World Journal of Clinical Oncology
Manuscript ID	104299
Country	China

Received	2024-12-16 14:01
Peer-Review Started	2024-12-16 14:01
To Make the First Decision
Return for Revision	2025-04-01 07:55
Revised	2025-04-11 13:55
Second Decision	2025-05-19 02:45
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-05-21 12:36
Articles in Press	2025-05-21 12:36
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2025-06-09 03:12
Publish the Manuscript Online	2025-06-20 08:05

ISSN	2218-4333 (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	Oncology
Manuscript Type	Review
Article Title	Comprehensive review of Bayesian network applications in gastrointestinal cancers
Manuscript Source	Invited Manuscript
All Author List	Min-Na Zhang, Meng-Ju Xue, Bao-Zhen Zhou, Jing Xu, Hong-Kai Sun, Ji-Han Wang and Yang-Yang Wang
Funding Agency and Grant Number	Funding Agency Grant Number Open Funds for Shaanxi Provincial Key Laboratory of Infection and Immune Diseases 2023-KFMS-1
Corresponding Author	Ji-Han Wang, Assistant Professor, PhD, School of Medicine, Xi'an International University, No. 18 Yudou Road, Yanta District, Xi'an 710077, Shaanxi Province, China. 513837742@qq.com
Key Words	Gastrointestinal cancers; Bayesian networks; Heterogeneous data integration; Early detection; Risk prediction; Prognosis; Personalized medicine
Core Tip	Bayesian networks (BN) provide a powerful framework for managing the complexity and uncertainty in gastrointestinal cancer research and clinical practice. By integrating diverse data types and modeling causal relationships, BN facilitate personalized treatment strategies. However, challenges such as data availability, computational demands, and clinical adoption must be addressed to fully unlock their potential for improving patient outcomes and quality of life.
Publish Date	2025-06-20 08:05
Citation	<p>Zhang MN, Xue MJ, Zhou BZ, Xu J, Sun HK, Wang JH, Wang YY. Comprehensive review of Bayesian network applications in gastrointestinal cancers. <i>World J Clin Oncol</i> 2025; 16(6): 104299</p>
URL	https://www.wjgnet.com/2218-4333/full/v16/i6/104299.htm
DOI	https://dx.doi.org/10.5306/wjco.v16.i6.104299

Full Article (PDF)	WJCO-16-104299-with-cover.pdf
Manuscript File	104299_Auto_Edited_062952.docx
Answering Reviewers	104299-answering-reviewers.pdf
Audio Core Tip	104299-audio.mp3
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Non-Native Speakers of English Editing Certificate	104299-non-native-speakers.pdf
Peer-review Report	104299-peer-reviews.pdf
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Scientific Editor Work List	104299-scientific-editor-work-list.pdf
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