ReviewiScience2025
Comprehensive application of artificial intelligence in colorectal cancer: A review.
Review in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Colorectal Cancer: Epidemiology, Risk Factors, Signaling Pathways, Clinical Features, Screening, Diagnosis, and Management.MedComm · 2026Review
- Assessment of Large Language Models in Colorectal Cancer Multidisciplinary Tumor Board Decision-Making: A Retrospective Single-Center Comparison of Guideline-Integrated General-Purpose vs. Domain-Specialized Models.Current oncology (Toronto, Ont.) · 2026Article
- Emerging Endorobotic and AI Technologies in Colorectal Cancer Screening: A Review of Design, Validation, and Translational Pathways.Diagnostics (Basel, Switzerland) · 2026Review
- Interpretable Machine Learning Models Based on Blood Cell-Derived Inflammatory Indices for Identifying Colorectal Neoplasia: A Retrospective Study.Journal of inflammation research · 2026Article
- Computer-assisted detection of colorectal polyps: a narrative review of clinical utility, ongoing limitations, and opportunities for advancement.Translational gastroenterology and hepatology · 2026Review
- The Role of Gut Microbiota in Colorectal Cancer Pathogenesis: A Comprehensive Literature Review.International journal of molecular sciences · 2025Review
- Could artificial intelligence-powered colonoscopies change the future of colorectal cancer screening?World journal of gastroenterology · 2025Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is increasingly integrated into the clinical management of colorectal cancer (CRC), playing a role in areas ranging from disease screening and therapy assistance to daily care and prognostic assessment. While AI's capabilities are clear, several challenges, including those related to ethics, data privacy, and deployment, must be addressed to fully realize its potential in driving innovation and advancing medical technologies. In this review, we provide a comprehensive summary of AI's applications in the clinical management of CRC, examine the areas in which it has been incorporated, and discuss the limitations and key considerations that will guide future research. Looking ahead, we believe AI's role in CRC management will only deepen, with the potential to contribute to personalized, overall clinical care and reshape the future of medicine.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.