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An AI Algorithm for Lymphocyte Focus Score of Minor Salivary Gland Biopsy Samples for Diagnosing Sjogren's Syndrome
Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Summary
The aim of this research is to discover an artificial intelligence (AI) algorithm for lymphocyte focus score in whole slide images of labial minor salivary gland (SG) biopsy samples for diagnosing Sjogren's Syndrome, in order to enhance the precision of pathological interpretation of labial minor SG biopsy samples in patients with suspected Sjogren's syndrome and aid clinicians make an accurate diagnose. A remote AI-assisted pathological interpretation platform for lymphocyte focus score in labial SG will be built for the global based on the research results. The research will propose the AI-assisted pathological interpretation of lymphocyte focus score in labial minor SG biopsy samples in the future guidelines for the diagnosis and treatment of Sjogren's syndrome. The research will: 1. Develop and debug the AI algorithm for lymphocyte focus score in whole slide images of labial minor SG biopsy samples for diagnosing Sjogren's Syndrome; 2. Internal test of the AI algorithm; 3. Clinical validation of the AI algorithm with blind method in multiple centers; 4)Built a remote AI-assisted pathological interpretation platform for lymphocyte focus score in labial SG for the global and Explore its clinical application.
Official title: An Artificial Intelligence Algorithm for Lymphocyte Focus Score in Whole Slide Images of Minor Salivary Gland Biopsy Samples for Diagnosing Sjogren's Syndrome : a Blinded Clinical Validation and Deployment Study
Key Details
Gender
All
Age Range
18 Years - 70 Years
Study Type
OBSERVATIONAL
Enrollment
1000
Start Date
2023-10-01
Completion Date
2024-09-30
Last Updated
2024-07-05
Healthy Volunteers
No
Conditions
Locations (1)
Ying-Qian Mo
Guangzhou, Guangdong, China