Pure Global AI
NCT06389019Recruiting

Whole-slide Image and CT Radiomics Based Deep Learning System for Prognostication Prediction in Bladder Cancer

Mingzhao XiaoClinicalTrials.govother
Verified
Study focus
Disease/Condition
Bladder Cancer
Drug/Device/Intervention
Deep learning system for prognostication prediction in bladder cancer
Study type
Observational
Intervention type
other
Sponsor & location
Primary sponsor
Mingzhao Xiao
Funder
First Affiliated Hospital of Chongqing Medical University
Location
Chongqing, China
Timeline & enrollment
Phase
N/A
Start date
Jan 01, 2024
End date
Oct 01, 2024
Enrollment
1000 participants
Primary outcome

Overall survival

Summary

Bladder cancer (BLCA), with its diverse histopathological features and varying patient
 outcomes, poses significant challenges in diagnosis and prognosis. Postoperative survival
 stratification based on radiomics feature and whole slide image feature may be useful for
 treatment decisions to improve prognosis. In this research, we aim to develop a deep
 learning-based prognostic-stratification system for automatic prediction of overall and
 cancer-specific survival in patients with BLCA.

ICD-10 classifications
Malignant neoplasm of bladderMalignant neoplasm: Bladder, unspecifiedMalignant neoplasm: Dome of bladderMalignant neoplasm: Overlapping lesion of bladderMalignant neoplasm: Lateral wall of bladder
Data source
Registry
ClinicalTrials.gov
Trial ID
NCT06389019
Type
Non-Device Trial
About this record

Access comprehensive clinical trial information for NCT06389019 through Pure Global AI's free database. This phase not specified trial is sponsored by Mingzhao Xiao and is currently Recruiting. The study focuses on Bladder Cancer. Target enrollment is 1000 participants.

This page provides complete trial specifications, intervention details, outcomes, and location information. Pure Global AI offers free access to ClinicalTrials.gov data, helping medical device and pharmaceutical companies navigate clinical research efficiently.