This project aims to leverage machine learning techniques for the early detection of heart disease, potentially saving lives through timely medical intervention. By analyzing a comprehensive dataset of heart disease risk factors, we aim to identify individuals at high risk, contributing to the broader goal of personalized medicine.
- Data Collection: Utilizing two datasets for comprehensive analysis.
- Data Preprocessing: Ensuring data quality and suitability for machine learning models.
- Model Training: Employing advanced machine learning models for accurate predictions.
- User Interface: A web-based interface for data input and prediction results.
- Database Integration: Storing user inputs and predictions for analysis and improvement.
To get started with this project, follow these steps:
- Clone the repository:
git clone https://github.com/Sachin_Mhetre/Heart_Disease_Prediction.git - Navigate to the project directory:
cd Heart_Disease_Prediction - Install dependencies (if any):
pip install -r requirements.txt - Run the application:
python app.py
📦Heart
┣ 📂instance
┃ ┗ 📜database.db
┣ 📂static
┃ ┣ 📂css
┃ ┃ ┣ 📜login.css
┃ ┃ ┣ 📜start.css
┃ ┃ ┗ 📜style.css
┃ ┣ 📂script
┃ ┃ ┗ 📜main.js
┃ ┣ 📜image1.png
┃ ┣ 📜image2.png
┃ ┣ 📜image3.png
┃ ┣ 📜logo.png
┃ ┣ 📜startpageheart.png
┃ ┣ 📜symbiosis.png
┃ ┗ 📜hearts-unscreen.gif
┣ 📂templates
┃ ┣ 📜dashboard.html
┃ ┣ 📜home.html
┃ ┣ 📜login.html
┃ ┣ 📜register.html
┃ ┣ 📜start.html
┃ ┗ 📜user_input_data.html
┣ 📜app.py
┣ 📜trained_model.pkl
┗ 📜requirements.txt
Login Page
Home Page
Dashboard Page
User Input Data Page
- Special thanks to contributors and supporters.
- Data sources: Heart Disease Database
To get a better understanding of how the project works, please watch the following video:
This video provides a comprehensive walkthrough of the project, demonstrating the user interface, data input process, and the prediction results. It's designed to give you a clear understanding of how the system works and how users can interact with it.