A Machine Learning Method for Predicting Disease Based on Symptoms

The dependency on computer-based technology has resulted in storage of lot of electronic data in the health care industry. As a result of which, health professionals and doctors are dealing with demanding situations to research signs and symptoms correctly and perceive illnesses at an early stage. However, Machine Learning technology have been proven beneficial in giving an immeasurable platform in the medical field so that health care issues can be resolved effortlessly and expeditiously. Disease Prediction is a Machine Learning based system which primarily works according to the symptoms given by a user. A robust machine learning model that can efficiently predict the disease of a human, based on the symptoms that he/she possess. This research work carried out demonstrates the disease prediction system developed using Machine learning algorithms such as Decision Tree classifier. The paper presents the comparative study of the results of the above algorithms used. The disease is predicted using algorithms and comparison of the datasets with the symptoms provided by the user. The accurate analysis of medical database benefits in early disease prediction, patient care and community services. The techniques of machine learning have been successfully employed in assorted applications including Disease prediction. .