Disease Prediction System in Human Beings using Machine Learning Approaches

Abstract

The disease prediction system predicts the disease by taking symptoms from the user and predict using machine learning algorithms that whether the user has disease or not. The proposed model supports the user-friendly interface and is easy to handle and performs operations accordingly. It is built to help the people at early stage to check the presence of disease, producing the results with an accuracy of almost 86% for Parkinson's disease, 97% for Gestational disease and 85% for cardiovascular disease. Our methodology is performing better in comparison of existing methods, where we have developed one algorithm for the same. The dataset of various patients related to this disease is taken from Kaggle websites. We represented our results with various diagrams and charts as well.