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5/21/2025 12:36:42 PM | Browse: 2 | Download: 0
Publication Name World Journal of Clinical Oncology
Manuscript ID 104299
Country China
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.
Citation Zhang MN, Xue MJ, Zhou BZ, Xu J, Sun HK, Wang JH, Wang YY. Comprehensive review of Bayesian network applications in gastrointestinal cancers. World J Clin Oncol 2025; In press
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
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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