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Artificial Intelligence-assisted HER2 Expression Assessment in Urothelial Carcinoma Based on Imaging-pathology Omics
Sponsor: Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Summary
This study aims to build upon previous research by using artificial intelligence methods to fuse multimodal data from imaging and pathology to construct a predictive model for HER2 expression in urothelial carcinoma. The model's performance will be validated and optimized using a multicenter cohort study, ultimately achieving accurate and rapid prediction of HER2 expression. This will guide precise decision-making for further HER2-targeted therapy and improve patient prognosis. Big data analysis and deep learning will also assist physicians in more accurately diagnosing the disease and developing personalized treatment plans. The research findings will promote the integration and development of artificial intelligence technology with the healthcare industry in the application of multimodal data from clinical, imaging, and pathology perspectives.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
4000
Start Date
2026-03-02
Completion Date
2030-06-03
Last Updated
2026-03-06
Healthy Volunteers
No
Conditions
Locations (1)
National Cancer Center / Cancer Hospital, Chinese Academy of Medical Sciences Beijing
Beijing, Chaoyang District, China