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Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome in Muscle Invasive Bladder Cancer
Sponsor: First Affiliated Hospital of Chongqing Medical University
Summary
Muscle invasive bladder cancer (MIBC) has a poor prognosis even after radical cystectomy. Postoperative survival stratification based on radiomics and deep learning may be useful for treatment decisions to improve prognosis. This study was aimed to develop and validate a deep learning radiomics model based on preoperative enhanced CT to predict postoperative survival in MIBC.
Official title: Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome From Preoperative CT in Muscle Invasive Bladder Cancer
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
500
Start Date
2023-08-01
Completion Date
2025-06-01
Last Updated
2025-05-31
Healthy Volunteers
No
Conditions
Interventions
develop and validate a deep learning radiomics model based on preoperative enhanced CT image
develop and validate a deep learning radiomics model based on preoperative enhanced CT to predict postoperative survival in MIBC
Locations (1)
Department of Urology, The First Affiliated Hospital of Chongqing Medical University
Chongqing, Chongqing Municipality, China