Real-time Skin Disease Prediction System using Deep Learning Approach

Abstract

Skin illness affects a large percentage of the world's population. The proposed study proposed a deep learning-based model for skin disease predication, In the traditional system it was time taking to predict the result and the accuracy is not accurate, Different machine learning methods can be used to classify skin disorders. In this study, we used machine learning algorithms to categories skin disease classes using ensemble approaches, and then used a feature selection method to compare the findings produced. Specialist can detect the disease type with the help of a web-based framework which is developed in Python Django frame- work. In the proposed study, we present a novel approach to detect the skin disease. Here we have used Support Vector Machine (SVM) Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) classifiers to identify the disease. Specialist need to upload the image and Deep learning algorithms will predict the disease and display the accuracy. The proposed model is easy to use, but it also provides a higher level of accuracy than previous methods. As a result of this model, we were able to achieve a 95% accuracy rate in the diagnosis of various skin conditions. The proposed system provides a state of art accuracy for early skin disease detection