expert system

Project Title: Heart Disease Prediction System Description: A smart and user-friendly Heart Disease Prediction System designed to estimate the likelihood of heart disease based on key health indicators. The system takes user inputs such as age, cholesterol level, blood pressure, lifestyle habits (exercise), and smoking status, then analyzes the data using machine learning techniques to provide a prediction. The interface is built with simplicity and usability in mind, allowing users to easily adjust values using sliders and dropdown menus. The system delivers fast and clear results, making it suitable for both educational and practical health awareness purposes. Key Features: Interactive UI with sliders for numerical inputs Support for lifestyle factors (exercise & smoking) Real-time prediction based on user input Clean and responsive design Easy to use for non-technical users Technologies Used: Python (Machine Learning Model) Streamlit (Frontend Interface) Scikit-learn (Model Training & Prediction) Objective: To provide an intelligent tool that helps users assess potential heart disease risk quickly and raise awareness about important health factors.