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Evaluating AI and Human Expert Decisions in Colorectal Cancer
Sponsor: Peking University Cancer Hospital & Institute
Summary
The goal of this observational study is to evaluate the decision-making consistency between large language models (LLMs) and expert multidisciplinary teams (MDTs) in adult patients diagnosed with colorectal cancer who underwent MDT consultation between January 2023 and December 2024. The main questions it aims to answer are: How consistent are the treatment decisions generated by LLMs compared to actual MDT decisions? Do different LLMs (e.g., ChatGPT, DeepSeek) show varying levels of agreement with expert recommendations? What clinical factors contribute to differences between AI-generated and human expert decisions? Researchers will compare the AI-generated treatment recommendations with real-world MDT decisions using anonymized patient records to see if LLMs can reliably support clinical decision-making in oncology. Participants will: Have their de-identified clinical data (e.g., imaging, pathology, MDT notes) processed through several LLMs Not be contacted or receive any interventions, as this is a retrospective study using existing clinical records only.
Official title: Comparison of Large Language Models and Expert Multidisciplinary Team Decisions in Colorectal Cancer
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
1500
Start Date
2025-07-01
Completion Date
2026-06-01
Last Updated
2025-07-01
Healthy Volunteers
No
Conditions
Interventions
LLM-MDT
Leveraging large language models (LLMs) to Generate Multidisciplinary Team (MDT) Treatment Recommendations
Locations (1)
Peking University Cancer Hospital
Beijing, China