Machine Learning for Predicting Colorectal Cancer and Advanced Colorectal Polyps: A Systematic Review and Meta-Analysis

Department

Internal Medicine

Document Type

Article

Publication Title

Journal of Clinical Gastroenterology

Abstract

Introduction: Machine learning (ML) has become increasingly pivotal in health care, particularly in colorectal cancer (CRC) detection and diagnosis with the use of predictive models and artificial intelligence-assisted colonoscopies. This study evaluates the efficacy of ML models in predicting the risk for CRC and advanced colorectal polyps (ACP) before colonoscopy.

Methods: A systematic literature review was conducted following PRISMA guidelines, focusing on studies using ML for CRC and ACP prediction. Data extraction regarding study type, ML methodology, quality of data, and bias assessment was in line with the CHARMS checklist. Meta-analysis was also performed to assess the performance of models for the prediction of CRC, adenoma, or both.

Results: This systematic review included 14 studies with 3618 median patients (333 to 263,879). Our study demonstrated considerable heterogeneity in methodologies and outcomes, with area under the receiver operating characteristic (AUROC) ranging from 0.6 to 1. The derivation+validation cohorts showed a pooled sensitivity of 0.832 (95% CI: 0.755-0.889) and specificity of 0.802 (95% CI: 0.722-0.863), with an overall AUROC of 0.883.

Conclusion: The review underscores the significant role of ML in CRC and ACP diagnosis and its routine use could efficiently direct high-risk patients to timely colonoscopies and spare the low-risk ones from unnecessary procedures. Despite the promise shown, the variability in methodologies and outcomes highlights the need for standardized approaches and further investigation in this field.

First Page

237

Last Page

246

DOI

10.1097/MCG.0000000000002172

Volume

60

Issue

3

Publication Date

3-1-2026

Publisher

Raven Press

Medical Subject Headings

Humans; Colorectal Neoplasms; Machine Learning; Colonoscopy; Colonic Polyps; Adenoma; Predictive Value of Tests; ROC Curve; Early Detection of Cancer

PubMed ID

40434809

Link to Full Text

Share

COinS