AI-based risk and subtype prediction for basal cell carcinoma using dermoscopic images

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 retrospective observational study develops a convolutional neural network to classify basal cell carcinoma risk and predict histopathological subtypes using clinical and dermoscopic images. Data are drawn from histopathologically confirmed BCC cases, with all information anonymized prior to analysis. The dataset is split into training, validation, and test sets while ensuring patient-level separation to prevent data leakage. The model's performance will be compared to that of dermatology physicians using the histopathology diagnosis as the reference standard. The goal is to determine whether AI can assist in risk stratification and subtype identification to inform treatment decisions.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* Patients with histopathologically confirmed basal cell carcinoma.
* Cases with a specified histopathological subtype.
* Availability of dermoscopic images with sufficient image quality and resolution for artificial intelligence analysis.

Exclusion Criteria:

* Cases without histopathological confirmation of basal cell carcinoma.
* Cases with unspecified histopathological subtype.
* Images with insufficient quality or resolution for artificial intelligence analysis.
* Cases without available dermoscopic images.

Where it's running

• Istanbul Training and Research Hospital
  Istanbul, Istanbul, Turkey (Türkiye) Recruiting

Study contacts

• Principal investigator: Ayse Esra Koku Aksu, MD — Istanbul Training and Research Hospital
• Study coordinator: Tugce Nur Izbudak Kara, MD
• Email: eizbudak@icloud.com
• Phone: +905395976598

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

• Methionine-Reduced Diet in Solid Tumors (early-phase)

  A small pilot study will test whether a methionine-reduced diet can change blood levels in adults with various solid tumors who are receiving standard cancer therapy.

  Recruiting Early Phase 1 University of California, Irvine · Orange, California · NCT07628634

• In-home cancer treatment with remote specialist support for patients in the Florida Panhandle

  This program will try giving standard cancer treatments at home to people living in the Florida Panhandle and nearby areas to see if they prefer it and have better treatment satisfaction.

  Recruiting Phase 2 Mayo Clinic · Jacksonville, Florida · NCT07285044

• Vitamin D and light therapy to boost skin cancer response before surgery

  This study tests whether giving Vitamin D or a placebo around the time of a light-based treatment (PDT) can help boost skin cancer treatment before Mohs surgery or ED&C in adults with basal cell or squamous cell carcinoma.

  Recruiting Case Comprehensive Cancer Center · Cleveland, Ohio · NCT07241585

• Using line-field confocal OCT to map Mohs surgery margins for basal cell carcinoma

  This tests whether line-field confocal optical coherence tomography (LC-OCT) can noninvasively show the edges of basal cell carcinomas in adults scheduled for Mohs surgery.

  Recruiting Roswell Park Cancer Institute · Buffalo, New York · NCT07182240

• Neoadjuvant Opdualag (nivolumab + relatlimab) versus nivolumab for resectable high-risk basal cell carcinoma

  This trial tests whether adding relatlimab to nivolumab before surgery helps people with resectable high‑risk basal cell carcinoma shrink tumors and improve surgical outcomes.

  Recruiting at 3 sites Phase 2 University of California, San Diego · Irvine, California and 2 other locations · NCT06624475

• AI-assisted confocal imaging to guide removal of basal cell carcinoma

  This project tests whether an AI tool can analyze confocal microscope images during basal cell carcinoma surgery to give surgeons real-time guidance on which tissue to remove.

  Recruiting LMU Klinikum · Munich, Bavaria · NCT06600165

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.