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©The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jan 7, 2026; 32(1): 111428
Published online Jan 7, 2026. doi: 10.3748/wjg.v32.i1.111428
Published online Jan 7, 2026. doi: 10.3748/wjg.v32.i1.111428
Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine
Chahat Suri, Department of Oncology, University of Alberta, Edmonton T6G 2R3, Alberta, Canada
Yashwant K Ratre, Department of Biotechnology, Guru Ghasidas Vishwavidyalaya, Bilaspur 495001, Chhattisgarh, India
Babita Pande, School of Studies in Life Science, Pt. Ravishankar Shukla University, Raipur 492010, Chhattisgarh, India
LVKS Bhaskar, Department of Zoology, Guru Ghasidas Vishwavidyalaya, Bilaspur 495001, Chhattisgarh, India
Henu K Verma, Department of Bioscience and Biomedical Engineering Indian Institute of Technology, Bhilai 491002, Chhattisgarh, India
Co-first authors: Chahat Suri and Yashwant K Ratre.
Author contributions: Verma HK lead the study; Suri C, Ratre YK were involved in the data collection and validation, provided the first draft of the manuscript; Ratre YK and Pande B prepared the figures and tables; Suri C, Ratre YK, Verma HK and Bhaskar L wrote and finalized the manuscript; Verma HK and Bhaskar L designed the outline and coordinated the writing of the paper; all authors have read and agreed to the published version of the manuscript.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
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/
Corresponding author: Henu K Verma, PhD, Assistant Professor, Department of Bioscience and Biomedical Engineering Indian Institute of Technology, Kutelabhata, Bhilai 491002, Chha
Received: July 10, 2025
Revised: August 23, 2025
Accepted: November 20, 2025
Published online: January 7, 2026
Processing time: 190 Days and 6.6 Hours
Revised: August 23, 2025
Accepted: November 20, 2025
Published online: January 7, 2026
Processing time: 190 Days and 6.6 Hours
Core Tip
Core Tip: Gastrointestinal (GI) cancers remain a major global health burden, demanding better early detection and personalized treatments. Recent artificial intelligence (AI) advances enable precision oncology by integrating diverse data from endoscopic images to genomic profiles. AI-driven tools enhance polyp detection, tumor grading, and multi-omics analysis for tailored therapies. Despite challenges in standardization and clinical adoption, these innovations promise to reduce diagnostic disparities and improve outcomes in GI cancer care.