Publication Name	Artificial Intelligence in Cancer
Manuscript ID	124432
DOI	10.35713/aic.124432
Country	Egypt

Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Artificial intelligence in colorectal liver metastases: From detection and resectability to treatment response and recurrence prediction
Manuscript Source	Unsolicited Manuscript
All Author List	Ahmed Salman, Ahmed Elewa and Mohamed AbdAlla Salman
Funding Agency and Grant Number
Corresponding Author	Ahmed Salman, FRACP, FRCP, Internal Medicine, Kasr Alainy School of Medicine, 1 Al-Saray Street, Al-Manial, Cairo 3178, Al Qāhirah, Egypt. awea844@gmail.com
Key Words	Colorectal liver metastases; Artificial intelligence; Radiomics; Deep learning; Machine learning; Precision oncology
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.
Citation	Salman A, Elewa A, Salman MA. Artificial intelligence in colorectal liver metastases: From detection and resectability to treatment response and recurrence prediction. Artif Intell Cancer 2026; In press DOI: https://doi.org/10.35713/aic.124432
PDF	124432-in-press.pdf

Received	2026-06-15 03:42
Peer-Review Started	2026-06-15 03:42
First Decision by Editorial Office Director
Return for Revision	2026-07-15 06:51
Revised	2026-07-23 23:37
Publication Fee Transferred
Second Decision by Editor	2026-07-30 02:32
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-07-30 10:47
Articles in Press	2026-07-30 10:47
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2644-3228 (online)
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