Skin Disease Identification Using Machine Learning

Abstract

The timely identification of melanoma, the most aggressive type of skin cancer, is essential for effective treatment and enhanced survival rates. This study introduces Derm Detect, an advanced system that merges deep learning-based image analysis with a voice-enabled chatbot to aid in the initial diagnosis of skin cancer. The system employs a Convolutional Neural Network (CNN) for the automated classification of dermoscopic images, achieving a 92. I % accuracy rate in differentiating between benign and malignant lesions. Furthermore, a chatbot powered by Natural Language Processing (NLP) is incorporated to engage with users, respond to medical inquiries, and perform guided symptom assessments using both text and voice formats. The design of the system is modular, user-friendly, and has been thoroughly tested to guarantee optimal performance and scalability.