Heart Disease Prediction System Project Description This project is an AI-powered application designed to predict the likelihood of a person having heart disease based on their medical data. The system uses machine learning classification models trained on a publicly available medical dataset to provide predictions through a professional, user-friendly web interface.
This application was developed as a portfolio project to demonstrate skills in data preprocessing, machine learning model building, and full-stack web application development with Python.
Key Features Predictive Modeling: Utilizes powerful classification algorithms (e.g., Random Forest, XGBoost) to predict heart disease.
Data Imputation: The model is built to handle incomplete data, making predictions even when some information is missing.
User-Friendly Interface: A clean, modern, and responsive UI built with HTML, CSS, and Flask allows for easy user interaction.
Local Deployment: The application can be run locally on any machine with Python and the necessary libraries.
How to Run the Project Follow these steps to set up and run the application on your local machine.
Prerequisites Ensure you have Python 3.x and pip installed.
Installation Clone the repository or download the project files.
Navigate to the project's root directory in your terminal.
Install the required Python libraries using the requirements.txt file:
Bash
pip install -r requirements.txt If the model file (heart_disease_model.pkl) is not present, you can generate it by running the model-building script:
Bash
python model_building.py Running the Application From the root directory, run the Flask application:
Bash
python app.py Open your web browser and go to the following address:
http://127.0.0.1:5000 Technology Stack Python: The core programming language.
Flask: A lightweight web framework for the back-end.
scikit-learn: For building and evaluating machine learning models.
Pandas & NumPy: For data manipulation and numerical operations.
Seaborn & Matplotlib: For data visualization.
HTML & CSS: For the front-end user interface.
Disclaimer This application is for educational purposes only. It is not intended to provide medical advice or a diagnosis. The predictions are based on a machine learning model trained on a specific dataset and may not be accurate. Always consult a qualified healthcare professional for any health-related concerns.
Author Pranshu Saraswat# CodeAlpha-Heart-Disease-Prediction-System-Task3