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 Endosc. Mar 16, 2026; 18(3): 116381
Published online Mar 16, 2026. doi: 10.4253/wjge.v18.i3.116381
Published online Mar 16, 2026. doi: 10.4253/wjge.v18.i3.116381
Artificial intelligence in predicting colorectal polyp histology: Systematic review and meta-analysis of diagnostic accuracy in real-time procedures
Princess Curlej, Department of Gastroenterology, University of South Wales in Association with Learna Ltd., Cardiff CF37 1DL, United Kingdom
Jonathan Soldera, Department of Gastroenterology and Acute Medicine, University of South Wales in Association with Learna Ltd., Cardiff CF37 1DL, United Kingdom
Jonathan Soldera, Department of Gastroenterology, Logan Hospital, Brisbane 4131, Queen
Co-first authors: Princess Curlej and Jonathan Soldera.
Author contributions: Curlej P and Soldera J participated in the concept and design research, drafted the manuscript, contributed to data acquisition, analysis and interpretation, and they contributed equally to this manuscript and are co-first authors; Soldera J contributed to study supervision. All authors contributed to critical revision of the manuscript for important intellectual content.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Corresponding author: Jonathan Soldera, MD, PhD, Tutor, Department of Gastroenterology and Acute Medicine, University of South Wales in Association with Learna Ltd., 86-88 Adam Street, Cardiff CF37 1DL, United Kingdom. jonathansoldera@gmail.com
Received: November 11, 2025
Revised: December 10, 2025
Accepted: January 20, 2026
Published online: March 16, 2026
Processing time: 123 Days and 4.9 Hours
Revised: December 10, 2025
Accepted: January 20, 2026
Published online: March 16, 2026
Processing time: 123 Days and 4.9 Hours
Core Tip
Core Tip: Artificial intelligence enables accurate, real-time differentiation between neoplastic and non-neoplastic colorectal polyps, fulfilling the optical biopsy criteria. By supporting “resect-and-discard” strategies for diminutive lesions and providing decision assistance to less experienced endoscopists, artificial intelligence can streamline colonoscopy workflows, mitigate pathology workloads, and enhance colorectal cancer prevention programs.