Pathology-Supported Artificial Intelligence-Based Comprehensive System for Early Diagnosis, Analysis, and Monitoring of Skin Cancer Lesions
Skin cancer, particularly melanoma, continues to rise globally, with early detection remaining challenging due to subtle visual patterns, limited specialist access, and increasing clinical workload. To address this need, the project proposes developing an advanced AI-based system for early and accurate skin cancer classification and monitoring, guided by dermatologists, surgeons, and pathologists to ensure clinical relevance. A high-quality dataset of approximately 6,000 clinical and public images will be expertly annotated, used to train robust machine learning models, and validated on 200 real-world hospital cases. Jointly led by Akdeniz University and the University of Jordan, the project will integrate coordinated data collection, algorithm development, and clinical evaluation, strengthened by an international collaboration that enhances dataset diversity and research impact. The resulting system aims to standardize diagnosis, reduce variability, improve early melanoma detection, and support broader national and regional efforts to advance AI-driven healthcare.