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Development and Validation of an AI Foundation Model for Frozen-Section Pathology
Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Summary
This multicenter observational study aims to develop and validate an artificial intelligence foundation model for frozen-section pathology. The study includes a retrospective phase and a prospective validation phase. Retrospective frozen-section pathology data will be used for model development, internal validation, and external validation. A prospective multicenter cohort of patients undergoing intraoperative frozen-section examination will then be enrolled to evaluate the model in a real-world clinical setting. The model will analyze digitized frozen-section whole-slide images and will be evaluated for prespecified frozen-section pathology diagnostic tasks across multiple organ systems. Its performance will be assessed using pathological reference standards. The primary outcome is the area under the receiver operating characteristic curve. Secondary outcomes include accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. This study is observational and will not require research-mandated changes to routine clinical care.
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
33000
Start Date
2026-04-27
Completion Date
2026-12-01
Last Updated
2026-07-16
Healthy Volunteers
No
Locations (1)
Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, Guangdong
Guangzhou, China