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Risk Classification and Prediction of Histopathological Subtypes in Basal Cell Carcinoma Using a CNN-Based Artificial Intelligence Model on Dermoscopic Images

Status: Recruiting
Location: See location...
Study Type: Observational
SUMMARY

This retrospective observational study aims to develop and evaluate a convolutional neural network (CNN)-based artificial intelligence model for risk classification and histopathological subtype prediction of basal cell carcinoma (BCC) using clinical and dermoscopic images. Histopathologically confirmed BCC cases from a dermatology archive will be included. The primary objective is to assess the diagnostic performance of the CNN model in classifying BCC as low-risk or high-risk. Secondary objectives include predicting histopathological subtypes and comparing the model's performance with that of dermatology physicians. Histopathological diagnosis will serve as the reference standard. All archived data will be anonymized before analysis.

Eligibility
Participation Requirements
Sex: All
Maximum Age: 100
Healthy Volunteers: f
View:

• 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.

Locations
Other Locations
Turkey
Istanbul Training and Research Hospital
RECRUITING
Istanbul
Contact Information
Primary
Tugce Nur Izbudak Kara, MD
eizbudak@icloud.com
+905395976598
Time Frame
Start Date: 2026-05-22
Estimated Completion Date: 2027-05-22
Participants
Target number of participants: 2500
Treatments
Low-Risk Basal Cell Carcinoma
Patients with histopathologically confirmed low-risk basal cell carcinoma, including nodular, superficial, pigmented, adenoid, solid, and nodulocystic subtypes. Clinical and dermoscopic images will be used for artificial intelligence-based risk classification and subtype prediction.
High-Risk Basal Cell Carcinoma
Patients with histopathologically confirmed high-risk basal cell carcinoma, including infiltrative, micronodular, morpheaform, and basosquamous subtypes. Clinical and dermoscopic images will be used for artificial intelligence-based risk classification and histopathological subtype prediction.
Related Therapeutic Areas
Sponsors
Leads: Istanbul Training and Research Hospital

This content was sourced from clinicaltrials.gov