Abstract
Skin diseases pose considerable health challenges for individuals with albinism. Early detection of skin conditions can be crucial for their well-being, given their vulnerability to precancerous and cancerous skin lesions due to the absence of pigmentation. This study aims to develop an artificial intelligence (AI) algorithm for classifying skin images and identifying disease patterns in albinism, thus enhancing early diagnosis and clinical management. We foresee constructing a publicly available skin disease dataset to train AI models, annotating images for albinism-related skin lesions: actinic keratosis, basal cell and squamous cell carcinoma, and conduct clinical validation using data from albinism patients in sub-Saharan Africa to refine diagnostic accuracy. The limited availability of qualified dermatologists in the region highlights the need for an effective AI solution to improve the speed and accuracy of diagnosing skin diseases while providing people with albinism with an accessible tool for self-detection of suspicious skin lesions.