Prediction of Dermatological Disease with Machine Learning

Dermatological disorders (DD) are widespread health issues in nations worldwide. The dangers of infections are hidden, and may lead to both mental and physical health problems. In severe circumstances, it might even result in skin cancer. Therefore, one of the most difficult jobs in medical image processing is to diagnose DD from clinical photographs. Additionally, diagnosing DD manually by medical professionals is time-consuming and arbitrary. Therefore, automatic DD prediction is necessary for both patients and dermatologists, which speeds up the planning of therapies. In this piece of writing, we reviewed the different types of DD, procedure uses for the identification and categorization of DD and their early identification by the help of various machine learning (ML) algorithms which gives their specific accuracy rate in which Convolutional Neural Network (CNN) shows the highest accuracy with the accuracy rate 99.05% respectively.