DERM-AI: Dermatological Disease Prediction Based on CNN Model

Skin cancer is a critical health concern that can spread rapidly if not identified and treated early. The applications of deep learning (DL) techniques, particularly convolutional neural networks (CNNs), have marked a significant advancement in dermatological disease diagnosis, with dermoscopic images being central to this progress. This research work provides a comprehensive research study of CNN-SVM based techniques for the classification of dermatological diseases. It discusses key aspects such as dataset preparation, model architecture selection, training approaches, and performance evaluation. Despite challenges like data scarcity, class imbalance, and model interpret-ability, the study aims to improve diagnostic accuracy and efficiency in dermatological care, ultimately benefiting patient outcomes and healthcare resource utilization.