Literature Survey of Skin Disease Detection & Treatment Recommendation System using Deep Learning

Literature Survey of Skin Disease Detection & Treatment Recommendation System using Deep Learning

Mr. Byregowda B K1, Nisha Kumari2, Shwetha B3, Naincy Priya4, Priyanshu Raj5

1Associate professor, Department of Information Science and Engineering, Sir M Visvesvaraya Institute of Technology, Bengaluru.

2,3,4,5 Department of Information Science and Engineering, Sir M Visvesvaraya Institute of Technology, Bengaluru.

Abstract - Millions of people worldwide suffer from skin conditions, which, if not identified and treated promptly, can result in serious health issues. The lack of dermatologists and the difficulty of visual diagnosis make timely detection difficult even with advancements in medical technology. In this project, we use Convolutional Neural Networks (CNN) and sophisticated architectures such as ResNet-50 to propose a deep learning-based system for automatic skin disease detection and treatment recommendation. The system categorizes illnesses, suggests treatments, and determines the severity to help users decide whether to see a doctor. In remote or underserved areas, this automated method can help medical professionals and be implemented as a scalable solution for early skin disease diagnosis.

Key Words:  Neural Network (CNN); ResNet-50; Treatment Recommendation System; HAM10000; DermNet.