E-HOMEOPATBIC HEALTHCARE SYSTEM

Abstract

The objective of this project is to develop a web application that will use scarped dataset of disease and symptoms in order to predict diseases of patients’ symptoms, also recommend them homeopathic medicines The usual process of diagnosis may not be adequate in the case of a severe illness. Developing a medical diagnosis method based on machine learning (ML) algorithms in predicting certain diseases can benefit in a more reliable diagnosis than the traditional method. We have developed a disease prediction system using multiple ML algorithms. The dataset utilized had more than 200+ diseases and 513+ symptoms for training the models. Based on the symptoms, the diagnosis system returns the output as the disease that the person might be suffering from. The weighted Logistic Regression algorithm returned the best results as compared to the other algorithms. The accuracy of the weighted Logistic Regression algorithm for the prediction was 93.5 %. Our diagnosis model can serve as a doctor for the initial diagnosis of a disease to ensure proper medication can be given on time and lives can be saved through recommended homeopathic medicines.