Skin cancer classification using vision transformers and explainable artificial intelligence
Getamesay Haile Dagnaw, Meryam El Mouhtadi, Musa Mustapha
Abstract
Background: Skin cancer diagnosis is a critical aspect of dermatological healthcare, and requires accurate and efficient classification methods. Recently, vision transformers (ViTs) and convolutional neural networks (CNNs) have emerged as promising architectures. However, the interpretability of these models remains a concern, hindering their widespread adoption in the clinical setting. Therefore, the aim of this research is to propose an explainable skin cancer classification using deep learning and explainable artificial intelligence methods.
Topics & Concepts
InterpretabilityArtificial intelligenceConvolutional neural networkDeep learningComputer scienceSkin cancerMachine learningArtificial neural networkCancerMedicineInternal medicineCutaneous Melanoma Detection and Management