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AI-Based Risk Classification and Histopathological Subtype Prediction of Basal Cell Carcinoma Using Dermoscopic Images

NCT07677124 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 2500

Last updated 2026-06-30

No results posted yet for this study

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.

Conditions

Sponsors & Collaborators

  • Istanbul Training and Research Hospital

    lead OTHER_GOV

Principal Investigators

  • Ayse Esra Koku Aksu, MD · Istanbul Training and Research Hospital

Eligibility

Min Age
0 Years
Max Age
100 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-05-22
Primary Completion
2027-05-22
Completion
2027-05-22

Countries

  • Turkey (Türkiye)

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07677124 on ClinicalTrials.gov