Disease Prediction System using Machine Learning

Abstract

Staying healthy is directly proportional to productive and energetic life. A system can be modeled to maintain the health track of a person and to avoid further health issues. Incorporating machine learning and artificial intelligence techniques in the medical sector can be of great benefit to healing millions of patient’s diseases and predicting disease at an early stage to decrease the mortality statistics which are rapidly increasing. This paper provides a survey and analysis of the various disease diagnostic systems proposed previously by various authors. In addition, it also proposes an application that predicts the vulnerability of the disease by giving primary symptoms and other clinical data of a person as parameters. Two algorithms Random Forest Classifier and K Nearest Neighbour Classifier are studied and explored for symptom analysis and disease prediction.