International Research Journal of Education and Technology

Skin diseases are among the most common health problems worldwide, affecting millions of people regardless of age, gender, or geographical location. Early detection and accurate diagnosis play a crucial role in preventing severe complications, especially in cases such as skin cancer. However, traditional diagnosis methods rely heavily on dermatologist expertise, which may not always be accessible in rural or underdeveloped areas. With the rapid advancement of Artificial Intelligence (AI) and Deep Learning, automated skin disease detection systems have emerged as a reliable and efficient solution for assisting medical professionals.

This journal presents a Skin Care Detection System developed using deep learning techniques, particularly Convolutional Neural Networks (CNNs), for identifying and classifying different types of skin conditions from images. The system is designed to analyze skin lesion images, extract relevant features, and predict the type of skin disease with high accuracy. The model is trained on labeled dermatological image datasets and deployed through a web-based interface for user-friendly interaction. The integration of AI in dermatology enhances diagnostic speed, reduces human error, and provides preliminary screening support.