Human Disease Prediction Using Machine Learning

Abstract: The Human Disease Prediction A machine learning system is based on predictive modeling and uses the symptoms the user enters into the system to predict the disease of the patient or user. The application has three login methods: user or patient login, doctor login, and administrator login. The tool evaluates the symptoms provided by the user or patient as input and provides the results of the disease as output based on predictive algorithms. A smart health assessment is done using a Naive Bayes classifier. The Naive Bayes classifier evaluates the probability of the disease, taking into account all subjects during the study period. Accurate interpretation of disease data facilitates patient/user disease prediction and provides users with a clear view of the disease. After the prediction, the user or patient can consult the specialist using the interactive window. It uses machine-learning algorithms and database management technology to extract new patterns from historical data. By using machine learning algorithms, prediction accuracy will be improved, and users or patients will have easy and convenient access to the application.