Large Language Models Assist in Tumor MDT

Recruiting now · Not applicable

Conditions studied: Lung Cancer, Breast Cancer, Colorectal Cancer, Stomach Cancer, Liver Cancer

In brief

Multidisciplinary teams (MDTs) represent the gold standard for personalized tumor treatment, but they are limited by medical resources and accessibility Limitation. Although large language models (LLMs) have shown promise in medical reasoning, their multidisciplinary practicality in pan-cancer MDTs has not been fully explored. In the early stage of this project, LLMs with high clinical application efficacy were identified through benchmark tests, and an open-label randomized controlled study (RCT) was conducted based on these LLMs. The research aims to explore whether AI-assisted assistance can enhance the accuracy and writing efficiency of MDT diagnosis and treatment reports. This study intends to prospectively collect the diagnosis and treatment information of 20 patients and MDT diagnosis and treatment information. It is planned to recruit 40 junior doctors. Doctors in the intervention group will use LLM to assist in the writing of MDT reports, while doctors in the control group will use traditional information retrieval methods for the writing of MDT reports. Three clinical experts ultimately used a standardized Likert scale to conduct comprehensive and multidisciplinary scoring of the MDT reports of the intervention group and the control group. This study quantitatively compared the diagnosis and treatment quality and efficiency of the MDT AI-assisted model and the traditional model to verify the application potential of large language models in assisting tumor diagnosis and treatment.

Key facts

Study ID

NCT07504367

Run by

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

People needed

60

Starts

2026-01-01

Expected to finish

2026-12-31

Last updated by the study team

2026-03-31

Who can join

Age: 25 and older, up to 33. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• A junior doctor with a practicing physician qualification certificate.
• Oncologists, surgeons, radiation oncologists, radiologists and pathologists with 3 to 5 years of clinical experience.
• Age: 25 to 33 years old, gender not limited.
• During the research period, one can participate for no less than 10 hours.
• Agree to participate in this research and sign the informed consent form.

You may not qualify if…

• Have participated in the previous diagnosis and treatment of any one of the 20 cases included in the study.

Where it is running

• Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University — Guangzhou, Guangdong, China (enrolling)
• Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University — Guangzhou, Guangdong, China (enrolling)

Full record on ClinicalTrials.gov

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