Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound: A Multicenter, Ambispective Cohort Study
NCT ID: NCT07111364
Last Updated: 2025-08-17
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
400 participants
OBSERVATIONAL
2025-05-27
2026-05-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
OTHER
Interventions
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observational diagnostic model development
observational diagnostic model development
Eligibility Criteria
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Exclusion Criteria
* Patients unable to undergo abdominal/transrectal ultrasound (e.g., uncooperative individuals, technically inadequate images);
* History of bladder tumor surgery, radiotherapy, chemotherapy, or systemic therapy within 3 months; ④ Patients with indwelling medical devices (e.g., double-J ureteral stents, urinary catheters);
* Failure to undergo bladder tumor surgery within 2 weeks post-ultrasound; ⑥ Non-urothelial carcinoma or pathologically unconfirmed diagnoses.
18 Years
85 Years
ALL
No
Sponsors
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Peking University First Hospital
OTHER
Responsible Party
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Locations
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Department of Urology, Peking University First Hospital
Beijing, , China
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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BCA-AI-US
Identifier Type: -
Identifier Source: org_study_id
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