Multiple Disease Prediction System

Abstract

In recent years, the rise of chronic diseases and health problems has created a pressing need for accurate and efficient disease prediction. The Corona virus pandemic further highlighted the importance of early disease detection and giving importance to early signs of symptoms. Further, many people experience symptoms of illnesses but are unsure about what disease or condition they might have. This uncertainty can lead to anxiety and stress, and sometimes people may delay seeking medical help until their symptoms worsen. Additionally, some people may not have easy access to health care services and facilities or may not want to visit a healthcare facility for various reasons. Taking all these factors into consideration, this paper proposes a multiple disease prediction system that allows users to enter their symptoms and get an indication of what they might be experiencing. The system facilitates early disease detection. Machine learning algorithms are utilized to analyze a symptom dataset which has hundreds of symptoms combinations for each disease. After training and development of machine learning models, they have been in corporate into a Stream lit application.