AI-based diagnostic tools for skin cancer have become increasingly popular due to their efficiency and low cost. However, a critical limitation of many existing models is their lack of diversity in training data—particularly the underrepresentation of darker skin tones. As a result, these models tend to perform poorly on non-white patients, increasing the risk of misdiagnosis or delayed diagnosis and contributing to significant health disparities. This project aims to address this issue by developing a diagnostic tool capable of accurately identifying malignant skin lesions across all skin tones