Smart Healthcare System Using Machine Learning for Predictive Diagnosis and Treatment Planning

Abstract - Early disease identification is crucial for prompt treatment and improved patient outcomes in the modern healthcare system. This study presents a machine learningbased disease prediction and medical recommendation system that analyses symptoms and offers precise health insights. A well- structured dataset comprising disease categories, suggested therapies, and symptom severity forms the foundation of the system. It provides individualized nutritional and medical advice by using a classification-based predictive model to analyse symptom patterns and propose potential diagnoses. We have created a web-based interface to make the system easier to use, enabling users to enter their symptoms and get immediate medical advice. This method allows users to conduct a preliminary self- evaluation prior to requesting expert assistance, thereby bridging the gap between patients and medical advice. This technology provides rapid and accurate health insights, making it an invaluable resource for well-informed healthcare decision- making.