Smart Multiple Disease Prediction System Using Machine Learning

This study brings into focus the development of a Smart Disease Prediction System based on machine learning approaches and techniques for the purpose of increased accuracy in the early identification of disease risks.The proposed system identifies predictions based on medical parameters and symptoms provided by the users for the risk associated with various diseases.To increase the accuracy levels for predictions, the study employs various supervised machine learning approaches.Based on the performance measures of the processing steps, the most apt approach for predictions on individual diseases can be derived.The designed system would be based on the development of an online application with an interactive interface for instant and efficient processing for non-IT individuals.The results obtained confirm that the application and use of machine learning approaches for disease prediction can contribute positively to the increased efficiency of early disease identification.