Disease Prediction Using Machine Learning

Abstract

The predictive modeling-based "Disease Prediction" framework predicts the user's disease based on the symptoms that the user offers as feedback to the system. The machine takes the user's symptoms as feedback and calculates the probability of the disease.

To predict disease, the Nave Bayes Classifier, Random Forest, and Decision Tree are used. The Nave Bayes Classifier is used to measure the disease risk. As a result, the average accuracy probability of prediction is 60%.