Various Disease Forecast Using Machine Learning and Streamlit

This research paper presents a machine learning based approach for predicting three major chronic diseases, Parkinson's, liver and heart diseases, as these are among the leading causes of morbidity and mortality worldwide. Early identification a nd managemento f these diseases a re critical for better outcomes and reduced healthcare costs. This purpose of this research paper is to develop accurate prediction models for these three diseases using machine learning algorithms based on patients' demographic, clinical, and lifestyle factors. Furthermore, the study underscores the potential of machine learning algorithms in disease prediction and management, highlighting the necessity for advanced technology in healthcare. This research paper findings indicate t he a ppropriate model suitable for various diseases based on Support Vector Machine, Random Forest Classifier a nd X GBoost algorithms.