ArticleBJS open2025
Concordance of ChatGPT artificial intelligence decision-making in colorectal cancer multidisciplinary meetings: retrospective study.
Article in BJS open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Large Language Models in Colorectal Cancer Care and Clinical Decision Support: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Concordance between GPT-4 and a multidisciplinary tumor board in pancreatic cancer: A prospective pilot study.Langenbeck's archives of surgery · 2026Article
- 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
- AI-driven qualitative skill assessment in laparoscopic training: a prospective observational study.NPJ digital medicine · 2026Article
- AI-driven smart patient retrieval for precision oncology.Nature reviews. Cancer · 2026Article
- Artificial Intelligence Language Models in Oncology: A Cross-Sectional Analysis of Published Studies.Cureus · 2026Review
- Therapeutic Decisions in Inflammatory Bowel Disease: ChatGPT-4.0 Compared to Medical Expertise.JGH open : an open access journal of gastroenterology and hepatology · 2026Article
- Comparing artificial intelligence and multidisciplinary tumor board decision making in real-world cancer care: a prospective blinded concordance study.ESMO real world data and digital oncology · 2026Article
- Article
- Clinical evaluation of large language model recommendations in melanoma: comparison with multidisciplinary tumor board decisions in a real-world cohort.Frontiers in oncology · 2026Article
- Artificial Intelligence and Multidisciplinary Oncology Decision-Making: A Systematic Review of LLM Concordance with MDT Recommendations and Implications for Clinical Reasoning Education.Advances in medical education and practice · 2026Review
- Artificial intelligence for perioperative precision in surgical oncology.Frontiers in surgery · 2026Review
- Artificial intelligence in colorectal cancer multidisciplinary decision-making: concordance, predictive support and clinical translation.Frontiers in oncology · 2026Review
- Article
- Large Language Models for Cardiovascular Disease, Cancer, and Mental Disorders: A Review of Systematic Reviews.Healthcare (Basel, Switzerland) · 2025Review
- Foundation models: Insights and implications for gastrointestinal cancer.World journal of gastroenterology · 2025Review
- Artificial intelligence in multidisciplinary tumor boards enhancing decision making and clinical outcomes in oncology.iScience · 2025Review
- Feeding intelligence: comparative evaluation of ChatGPT and clinical guidelines for nutritional management in head and neck cancer.Journal of translational medicine · 2025Article
- Large language models for clinical decision support in gastroenterology and hepatology.Nature reviews. Gastroenterology & hepatology · 2025Review
- Artificial Intelligence for the Diagnosis and Management of Cancers: Potentials and Challenges.MedComm · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe objective of this study was to evaluate the concordance between therapeutic recommendations proposed by a multidisciplinary team meeting and those generated by a large language model (ChatGPT) for colorectal cancer. Although multidisciplinary teams represent the 'standard' for decision-making in cancer treatment, they require significant resources and may be susceptible to human bias. Artificial intelligence, particularly large language models such as ChatGPT, has the potential to enhance or optimize the decision-making processes. The present study examines the potential for integrating artificial intelligence into clinical practice by comparing multidisciplinary team decisions with those generated by ChatGPT.
methodsA retrospective, single-centre study was conducted involving consecutive patients with newly diagnosed colorectal cancer discussed at our multidisciplinary team meeting. The pre- and post-therapeutic multidisciplinary team meeting recommendations were assessed for concordance compared with ChatGPT-4.
resultsOne hundred consecutive patients with newly diagnosed colorectal cancer of all stages were included. In the pretherapeutic discussions, complete concordance was observed in 72.5%, with partial concordance in 10.2% and discordance in 17.3%. For post-therapeutic discussions, the concordance increased to 82.8%; 11.8% of decisions displayed partial concordance and 5.4% demonstrated discordance. Discordance was more frequent in patients older than 77 years and with an American Society of Anesthesiologists classification ≥ III.
conclusionThere is substantial concordance between the recommendations generated by ChatGPT and those provided by traditional multidisciplinary team meetings, indicating the potential utility of artificial intelligence in supporting clinical decision-making for colorectal cancer management.
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