Implementation of Smart Health Prediction Using ML

Abstract

The "Smart Health Prediction Using Machine Learning" system uses predictive modelling to predict the disease of users or patients based on the symptoms that the user inputs into the system. User/patient, doctor, and admin are the three options for logging onto the application. The tool analyses the symptoms provided by the user or patient as input and returns the likelihood of the disease based on the algorithmic prediction. The Nave Bayes Classifier is employed to generate insightful health forecasts. The Nave Bayes Classifier determines the illness% probability by using all of its features that were trained during the training phase. For patients and users, an accurate interpretation of disease data helps with early disease prediction and provides them with a clear picture of the situation.