03.09.2026journal-article
Frontiers in Public Health
Explainable ensemble transfer learning for skin lesion classification with multi-method explainability validation
Introduction Skin cancer is among the most prevalent and life-threatening malignancies worldwide. Early and accurate detection significantly improves therapeutic outcomes. Automated classification of dermoscopic skin lesions remains challenging due to class imbalance, inter-class visual similarity, and lack of interpretable predictions. This study proposes an accurate and interpretable weighted soft voting ensemble for multi-class skin lesion classification. Methods A weighted soft voting ensemble of three heteroge …