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Evaluation of AI Large Models for Diagnosis and Treatment in Real-World Cases: Multicenter Retrospective Study
Sponsor: First Affiliated Hospital of Fujian Medical University
Summary
This multicenter retrospective study aims to evaluate the diagnostic and therapeutic performance of three large language models-ChatGPT, Gemini and Deepseek-using 800 archived inpatient medical records from urology departments across four tertiary hospitals. The study will focus on the accuracy and applicability of these models in disease recognition, preliminary diagnosis and treatment recommendation generation, in order to explore their potential value and limitations in supporting clinical decision-making in real-world settings.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
800
Start Date
2026-01-01
Completion Date
2026-06-01
Last Updated
2026-01-30
Healthy Volunteers
No
Conditions
Interventions
Large Language Model Assessment (ChatGPT, Gemini, DeepSeek)
De-identified inpatient medical records were retrospectively collected from the urology departments of four tertiary hospitals (200 cases per site, 800 in total). Each case included standardized clinical information such as demographics, chief complaint, history of present illness, past medical history, physical examination, laboratory and imaging findings, discharge diagnosis and treatment plan. To simulate the role of an AI system in a "first-visit physician" scenario, all diagnostic conclusions, differential diagnoses and treatment plans were removed before being input into the models. Three large language models (ChatGPT, Gemini and DeepSeek) were prompted with a standardized instruction: "Based on the above clinical information, provide your preliminary diagnosis, differential diagnoses and treatment recommendations." Each model generated outputs including (i) primary and secondary diagnoses, (ii) differential diagnosis lists with reasoning and (iii) preliminary treatment suggesti
Locations (1)
The First Affiliated Hospital of Fujian Medical University
Fuzhou, China