RecruitingNCT06474338

AI Detection of Bladder Tumors Under Endoscopy

Artificial Intelligence Detection of Bladder Tumors Under Endoscopy

Sponsor

Peking Union Medical College Hospital

Enrollment

1,000 participants

Start Date

Jan 1, 2024

Study Type

OBSERVATIONAL

Conditions

Bladder Tumor

Summary

The goal of this clinical trial is to learn if the AI algorithm can detect bladder tumors better than urologists under cystoscopy. It will also train the AI algorithm for bladder tumor detection. The main question it aims to answer is: Can AI algorithm achieve IOU value, precision, recall, false negative rate of bladder tumor detection similar to that of urologists? The cystoscopy video will be annotated by AI and urologists. Researchers will compare AI algorithm to urologists to see if Al algorithm has a similar capability as urologists do.

Eligibility

Min Age: 18 YearsMax Age: 100 Years

Plain Language Summary

Simplified for easier understanding

This study is testing whether artificial intelligence (AI) can help doctors more accurately detect bladder tumors during a cystoscopy — a procedure where a small camera is inserted into the bladder through the urethra. The AI analyzes the live video from the camera to flag areas that may be tumors, potentially reducing the chance of missing small or early-stage cancers. **You may be eligible if...** - You are having a cystoscopy procedure - The cystoscopy video is available for analysis - One or more bladder lesions (growths) can be seen during the procedure **You may NOT be eligible if...** - The cystoscopy video is not clear enough for the AI system to analyze Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Interventions

DIAGNOSTIC_TESTdetection by artificial intelligence

The bladder lesion(s) are detected by artificial intelligence algorithm.

DIAGNOSTIC_TESTdetection by urologists

The bladder lesion(s) are detected by urologists.

Locations(1)

Peking Union Medical College Hospital

Beijing, Beijing Municipality, China

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NCT06474338

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