Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastrointest Oncol. Aug 15, 2026; 18(8): 116357
Published online Aug 15, 2026. doi: 10.4251/wjgo.116357
Published online Aug 15, 2026. doi: 10.4251/wjgo.116357
Application of artificial intelligence in primary gastrointestinal lymphoma: Opportunities, development potential, and future directions
Zong-Xian Zhao, Department of Anorectal Surgery, Fuyang People’s Hospital, Fuyang 236000, Anhui Province, China
Author contributions: Zhao ZX designed and wrote the manuscript.
AI contribution statement: Regarding the use of artificial intelligence (AI), we only utilized DeepSeek for text polishing. No AI tools were employed for main text generation, translation, data analysis, or image creation in this study.
Conflict-of-interest statement: The author declare no conflict of interest in publishing the manuscript.
Corresponding author: Zong-Xian Zhao, MD, Department of Anorectal Surgery, Fuyang People’s Hospital, No. 501 Sanqing Road, Yingzhou District, Fuyang 236000, Anhui Province, China. 461901580@qq.com
Received: November 10, 2025
Revised: November 29, 2025
Accepted: January 6, 2026
Published online: August 15, 2026
Processing time: 266 Days and 5.1 Hours
Revised: November 29, 2025
Accepted: January 6, 2026
Published online: August 15, 2026
Processing time: 266 Days and 5.1 Hours
Core Tip
Core Tip: As pointed out by Yang et al, primary gastrointestinal lymphoma (PGIL) remains challenging in diagnosis and treatment, with misdiagnosis and suboptimal therapies persisting. Artificial intelligence (AI) shows great potential in optimizing PGIL’s diagnosis (radiomics, endoscopy, and pathology) and treatment (subtype identification, regimen selection, and complication prediction). However, AI faces hurdles like scarce standardized datasets, poor interpretability, and data security risks. With sustained research, cross-disciplinary collaboration, and standardized efforts, AI is expected to become a standard clinical tool to improve PGIL patient outcomes.