Affiliation:
1. Computer Science and System Engineering, Lendi Institute of Engineering and Technology, Vizianagaram, India
Abstract
Skin diseases are a major public health problem worldwide, requiring effective and timely diagnosis for effective treatment. In this paper, we present a new approach to automatically detect skin diseases using deep learning technology. The model we propose uses a Convolutional Neural Network (CNN) to analyze dermatological images with high accuracy, providing reliable and fast diagnosis. The system was trained on a variety of datasets to provide reliable performance across a variety of skin conditions. Experimental results show that the proposed model outperforms existing methods, demonstrating its potential for integration into clinical settings. Implementation of this deep learning-based skin disease detection system has the potential to revolutionize dermatological diagnostics and provide a cost-effective and scalable solution to improve patient care.
Reference17 articles.
1. Almeida M.A.M., Santos I.A.X. Classification Models for Skin Tumor Detection Using Texture Analysisin Medical Images. J. Imaging. 2020;6:51.
2. S. Arifin et al.Dermatological Disease Diagnosis Using Color-Skin Images
3. Czodrowski, P.: Count on kappa. J. Comput. Aided Mol. Des. 28(11), 1049–1055 (2014)
4. Ivan Bratchenko, Lyudmela Bratchenko, Yulia Khristoforova. ScienceDirect, November 2021.
5. Pawel Budura, Anna Platkowska and Joanna Czajowska. IEEE. July 2020