AI supported detection of bladder cancer: AI-model-supported detection of bladder cancer during white light cystoscopy
Study summary
This study is being conducted to investigate if an artificial intelligence support tool is non-inferior in detecting bladder cancer compared to the traditional method, standard white light cystoscopy (WLC). The researchers will compare how well the artificial intelligence tool and WLC perform in detecting bladder cancer through a controlled, organized testing process.
Eligibility
Sex
ALL
Min age
18 Years
Max age
—
Healthy volunteers
No
Inclusion Criteria:
* Men and women adults, age \>18 years old
Suspicion of primary or recurrent bladder cancer
Willingness to sign the Informed Consent Form (ICF) for the CI
Ability to comprehend the oral and written Patient Information Leaflet (PIL)
Exclusion Criteria:
* Not able or willing to sign the Informed Consent Form
Primary outcome measure(s)
Sensitivity of standard WLC compared to WLC assisted by the AI model evaluated with a non-inferiority margin of 5%. — 7 month To determine whether the AI model is non-inferior with regards to sensitivity compared to standard WLC in a randomized controlled trial.
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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