CNN-Powered Medical Image Analysis for Skin Disease Classification and Diagnosis

Abstract

Dermatological conditions significantly affect the well-being of a vast number of individuals, as nearly everyone encounters some form of skin disorder annually. The traditional diagnosis of these conditions relies heavily on manual analysis, which is both time-consuming and labor-intensive. Moreover, existing diagnostic methods often fall short in effectively identifying and analyzing a wide range of skin diseases. To address these limitations, this study proposes a real-time skin disease prediction framework utilizing computer-aided techniques, specifically data mining algorithms and Convolutional Neural Networks (CNNs). The proposed approach demonstrates superior accuracy compared to conventional methods, offering a more reliable and efficient solution for skin disease diagnosis.