A STUDY ON DERMATOLOGICAL DISEASES USING CLASSIFICATION APPROACHES

Machine learning algorithms are widely used in medicine. Breast cancer, kidney illness, thyroid disease, diabetes, cancer, erythemato-squamous diseases, and a variety of other ailments all can benefit from these machine algorithms. The erythemato-squamous diseases (ESD) are used for the subject of this study. The main issue is that only a trained dermatologist is capable of detecting and classifying such diseases. To classify ESD Various classification algorithms were applied specifically VF15, C4.5, SVM, KNN, Neural Networks, Ensemble classifier algorithms like random Forest, Gradient Boosting Machine, Boosting, Artificial Neural Network, Deep Learning, Fuzzy Neural Networks, Ensembling learning using deep learning, Convolutional Neural Networks (convNet) and many are used. Another approach is feature selection which is applied with these classification algorithms to obtain the finest accuracy. It is experimented that, Ensemble classifier algorithms, feed forward Neural Network, Random Forests, convNet and Derm2Vec are giving best training precision for the exact classification of skin diseases among all preferred.