Spots Global Cancer Trial Database for Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome in Muscle Invasive Bladder Cancer
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Trial Identification
Brief Title: Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome in Muscle Invasive Bladder Cancer
Official Title: Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome From Preoperative CT in Muscle Invasive Bladder Cancer
Study ID: NCT06092450
Conditions
Study Description
Brief 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.
Detailed Description:
Eligibility
Minimum Age:
Eligible Ages: CHILD, ADULT, OLDER_ADULT
Sex: ALL
Healthy Volunteers: No
Locations
Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, Chongqing, China
Contact Details
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