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.
Artif Intell Cancer. Sep 8, 2026; 7(1): 124432
Published online Sep 8, 2026. doi: 10.35713/aic.124432
Published online Sep 8, 2026. doi: 10.35713/aic.124432
Artificial intelligence in colorectal liver metastases: From detection and resectability to treatment response and recurrence prediction
Ahmed Salman, Internal Medicine, Kasr Alainy School of Medicine, Cairo 11562, Al Qāhirah, Egypt
Ahmed Elewa, General Surgery, National Hepatology and Tropical Medicine Liver Institute, Cairo 16A, Egypt
Mohamed AbdAlla Salman, General Surgery, Kasralainy School of Medicine, Cairo 11562, Egypt
Author contributions: Salman A contributed to the study conception, manuscript drafting, and critical revision; Elewa A contributed to manuscript revision and final approval of the manuscript; Salman MA drafted the final version of the manuscript. All authors have read and approved the final manuscript.
AI contribution statement: AI-based tools were used solely for language polishing and formatting assistance during manuscript preparation. No AI tool was used to generate research data, interpret results, formulate conclusions, or produce or select references. All AI-assisted content was critically reviewed and revised by the authors, who take full responsibility for the accuracy, originality, and integrity of the manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Ahmed Salman, FRACP, FRCP, Internal Medicine, Kasr Alainy School of Medicine, 1 Al-Saray Street, Al-Manial, Cairo 11562, Al Qāhirah, Egypt.
Received: June 15, 2026
Revised: July 23, 2026
Accepted: July 30, 2026
Published online: September 8, 2026
Processing time: 79 Days and 17.7 Hours
Revised: July 23, 2026
Accepted: July 30, 2026
Published online: September 8, 2026
Processing time: 79 Days and 17.7 Hours
Core Tip
Core Tip: Artificial intelligence is now applied across every phase of colorectal liver metastasis care, but its maturity is uneven. Automated detection and liver volumetry already match expert performance, while models predicting response, recurrence, and survival often flounder during external validation. But the question is no longer whether algorithms can learn clinically relevant patterns, but whether they survive beyond the cohort that produced them. Progress will involve prospective multi-institutional validation, reproducible features, and multimodal data integration that enhances, rather than replaces, multidisciplinary clinical judgment.