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https://github.com/ahmed-aladdiin/heart-health-inspector
A Machine-Learning powered web app to give you an inspection on whether you are well or might have a heart disease.
https://github.com/ahmed-aladdiin/heart-health-inspector
Last synced: 4 days ago
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A Machine-Learning powered web app to give you an inspection on whether you are well or might have a heart disease.
- Host: GitHub
- URL: https://github.com/ahmed-aladdiin/heart-health-inspector
- Owner: Ahmed-Aladdiin
- License: mit
- Created: 2024-09-12T05:26:06.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2024-09-12T08:15:00.000Z (2 months ago)
- Last Synced: 2024-09-12T18:14:18.583Z (2 months ago)
- Language: Jupyter Notebook
- Size: 612 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Heart Health Inspector
Heart Health Inspector is a machine learning project designed to predict heart disease based on various health metrics. The project includes a web application built with Flask to provide a user-friendly graphical interface for users to input their health data and receive predictions.
## Project Structure
```
.
├── .gitignore
├── app/
│ ├── app_ml/
│ │ ├── __init__.py
│ │ ├── models.py
│ │ └── routes.py
│ ├── app.py
│ ├── dockerfile
│ └── requirements.txt
├── data/
│ ├── cardiovascular_preprocessed_dataset.csv
│ ├── cardiovascular_raw_dataset.csv
│ ├── features_training_data_v2.csv
│ └── features_training_data.csv
├── Building_Models.ipynb
├── Data_Preprocessing.ipynb
├── Exploratory_Data_Analysis.ipynb
├── LICENSE
├── model/
├── test_model.ipynb
└── test_script.py
```
## Notebooks
- Data_Preprocessing.ipynb: Contains the steps to preprocess the raw data.
- Exploratory_Data_Analysis.ipynb: Provides insights into the data through various visualizations.
- Building_Models.ipynb: Details the process of building and training the machine learning models.
- test_model.ipynb: Used for testing the trained models with new data.
## Web Application
- app.py: The main entry point for the Flask application.
- app_ml/: Contains the machine learning model and preprocessing logic.
- models.py: Defines the model and preprocessing functions.
- routes.py: Defines the routes for the web application.
- init.py: Initializes the Flask application.
## Usage
Navigate into the ./app directory inside the project
`cd app`
### Install Requirements
The required Python packages are listed in requirements.txt. To install them, run:
```bash
pip install -r requirements.txt
```
## Run the app
1. Run the Web Application:
```bash
python app.py
```
The application will be available at http://localhost:5000.
2. Input Data: Enter your health metrics into the form on the web page and submit to receive a prediction.
3. Test the Model: Use test_script.py to test the model with a CSV file containing test data.
## License
This project is licensed under the MIT License. See the LICENSE file for more details.
## Acknowledgements
This project uses various open-source libraries and tools. Special thanks to the contributors of these projects.
---
Feel free to contribute to this project by submitting issues or pull requests. For any questions, please contact the project maintainers.