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Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound: A Multicenter, Ambispective Cohort Study

NCT07111364 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 400

Last updated 2025-08-17

No results posted yet for this study

Summary

This study aims to develop an ultrasound image-based deep learning system to enable automatic segmentation, T-staging, and pathological grading prediction of bladder tumors. It seeks to enhance the objectivity, accuracy, and efficiency of bladder cancer diagnosis, reduce reliance on physician experience, and provide support for precision medicine and resource optimization.

Conditions

Interventions

OTHER

observational diagnostic model development

observational diagnostic model development

Sponsors & Collaborators

  • Peking University First Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-05-27
Primary Completion
2026-05-01
Completion
2026-05-31

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07111364 on ClinicalTrials.gov