MULTIPLE HUMAN DISEASE PREDICTION MODEL

Abstract

Now days most of the people are having lots of health-related issues, due to lack of healthy food, proper sleep and daily exercise. So, on-time analysis of any health-related problem is important for the prevention and treatment of the illness. The traditional way ofS diagnosis is not sufficient for the treatment of serious disease. In this study we have developed a platform for the prediction of multiple diseases like heart disease and diabetes. By which patient can predict multiple diseases on single platform.

Multiple Disease Prediction using Machine Learning is a comprehensive project aimed at predicting various diseases. This project leverages machine learning algorithms such as Support Vector Machine (SVM) and Logistic Regression. The models are deployed using Streamlit Cloud and the Streamlit library, providing a user-friendly interface for disease prediction. The application interface comprises two diseases: heart disease and diabetes. Upon selecting a particular disease, the user is prompted to input the relevant parameters required for the prediction model. Once the parameters are entered, the application promptly generates the disease prediction result, indicating whether the individual is affected by the disease or not. This project addresses the need for accurate disease prediction using machine learning techniques, allowing for early detection and intervention. The user-friendly interface provided by Streamlit Cloud and the Streamlit library enhances accessibility and usability, enabling individuals to easily assess their risk for various diseases. The high accuracies achieved by the different models demonstrate the effectiveness of the employed machine learning algorithms in disease prediction.