RECRUITINGOBSERVATIONAL
Bladder Cancer Detection Using Convolutional Neural Networks
About This Trial
The investigators aim to experiment and implement various deep learning architectures to achieve human-level accuracy in Computer-aided diagnosis (CAD) systems. In particular, the investigators are interested in detecting bladder tumors from CT urography scans and cystoscopies of the bladder in this project.
Who May Be Eligible (Plain English)
Who May Qualify:
- Patients with first time hematuria
- Patients with the control program for previous bladder cancer
Who Should NOT Join This Trial:
- Patients with control cystoscope for noncancer suspected disease
Always talk to your doctor about whether this trial is right for you.
Original Eligibility Criteria
View original clinical language
Inclusion Criteria:
* Patients with first time hematuria
* Patients with the control program for previous bladder cancer
Exclusion Criteria:
* Patients with control cystoscope for noncancer suspected disease
Treatments Being Tested
DIAGNOSTIC_TEST
Al_bladder
Detection of bladder tumor with help of Artificial intelligence
Locations (1)
Zealand University Hospital
Roskilde, Denmark