Detecting kidney cancer using advanced machine learning techniques

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This project focuses on utilizing deep learning architectures, specifically convolutional neural networks (CNN), to enhance the accuracy of computer-aided diagnosis (CAD) systems for renal cancer detection. The study aims to classify renal tumors from CT urography scans into various categories, including cancerous and non-cancerous types, while minimizing false positives. By automating the detection process, the study seeks to significantly reduce the time required for radiologists to create large-scale labeled datasets, ultimately improving diagnostic efficiency and accuracy.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* All patient with RCC, who underwent surgery

Exclusion Criteria:

* Patients with RCC, who did not underwent surgery

Where it's running

• Zealand University Hospital
  Roskilde, Denmark Recruiting

Study contacts

• Study coordinator: Nessn Azawi, Phd
• Email: nesa@regionsjaelland.dk
• Phone: 004526393034

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.