Skin Disease Detection and Recommendation

This paper presents a machine learning-based skin disease detection and recommendation algorithm designed to improve the accuracy and efficiency of skin disease detection Due to the increasing prevalence of skin disease, traditional approaches diagnosis often relies on cognitive assessment, which can lead to misdiagnosis and delay in treatment Through the use of applications machine learning algorithms to faces including Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) to analyze complete data of dermatologist images to achieve high classification accuracy. The system not only identifies various skin lesions but also provides appropriate treatment recommendations through a user-friendly interface. By increasing the accuracy of assessment and empowering patients through usable methods, this new approach aims to facilitate timely medical interventions for patients. All results have improved. Future research will focus on expanding the database and refining the algorithm to further advance the system’s capabilities for real-time analysis in clinical settings.