Heart Disease Prediction Model

Overview

This repository contains the source code and implementation for a heart disease prediction model deployed on Flask. The machine learning model predicts the likelihood of heart disease based on input features such as age, gender, various health metrics, and test results.

Table of Contents

• Features
• Installation
• Usage
• License

Features

• Flask web application for heart disease prediction
• Pre-trained machine learning model
• User-friendly web interface
• Input validation and error handling
• Complete backend integration
• Complete database integration

Installation

1. Clone the repository:

   git clone https://github.com/XDFrost/Heart-Disease-Prediction-Model.git

2. Change into the project directory:

   cd Heart-Disease-Prediction-Model

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Add uri and app passwords to config.json file. Make a .env file and add variables in it

   Required variables for .env file:

   1. production_URI
   2. secret_key
   3. MAIL_USERNAME
   4. MAIL_PASSWORD

2. Start the Flask application:

   python app.py

3. Open your web browser and go to http://localhost:5000

4. Use the web interface to input the required features and get predictions.

License

This project is licensed under the MIT License - see the LICENSE file for details.