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AI-Assisted Pathologist Performance Improvement: A Multicenter, Prospective, Randomized Controlled Trial
Sponsor: Nanfang Hospital, Southern Medical University
Summary
The investigators plan to conduct a multicenter, prospective, randomized controlled trial to systematically evaluate the added value of pathology-based AI models in the gastric cancer diagnostic workflow. The study will focus on comparing AI-assisted platform interpretation with conventional independent slide reading in terms of diagnostic accuracy (e.g., AUC), reading efficiency (e.g., comparison of time to diagnosis), quality of diagnostic reports, diagnostic confidence (Likert scale), and pathologists' satisfaction with the AI models. The investigators will also assess superiority for less-experienced (junior) pathologists and noninferiority for more-experienced (senior) pathologists. Successful completion of this project will provide high-level prospective evidence to support the standardized deployment, quality control, and broader application of pathology AI in the gastric cancer care pathway.
Official title: Artificial Intelligence Model-Assisted Improvement of Pathologists' Performance in Clinical Diagnostic Tasks: A Multicenter, Prospective, Randomized Controlled Trial
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
1000
Start Date
2025-11-01
Completion Date
2027-11
Last Updated
2026-02-10
Healthy Volunteers
No
Conditions
Interventions
AI pathology model
Doctors in this group are required to use the AI pathology model to assist their diagnoses. The AI pathology model will provide a predicted result for each case.
Control
Pathologists will independently diagnose each case based on their own clinical experience, and will record both their time to diagnosis and their diagnostic confidence.
Locations (2)
Nanfang Hospital, Southern Medical University
Guangzhou, Guangdong, China
The First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, China