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RECRUITING
NCT06437652

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

View on ClinicalTrials.gov

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

Locations (1)

Ying-Qian Mo

Guangzhou, Guangdong, China