https://github.com/msparihar/kidney-disease-prediction
This web application utilizes cutting-edge artificial intelligence to help people understand their risk of developing kidney disease. Developed with user-friendliness in mind, this tool allows individuals to easily enter their information and receive a personalized risk assessment.
https://github.com/msparihar/kidney-disease-prediction
classification computer-vision mlops-project python tensorflow
Last synced: about 2 months ago
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This web application utilizes cutting-edge artificial intelligence to help people understand their risk of developing kidney disease. Developed with user-friendliness in mind, this tool allows individuals to easily enter their information and receive a personalized risk assessment.
- Host: GitHub
- URL: https://github.com/msparihar/kidney-disease-prediction
- Owner: Msparihar
- License: mit
- Created: 2023-10-17T09:36:45.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-02-02T18:12:48.000Z (over 2 years ago)
- Last Synced: 2025-08-03T23:56:37.734Z (10 months ago)
- Topics: classification, computer-vision, mlops-project, python, tensorflow
- Language: Python
- Homepage:
- Size: 51.4 MB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Kidney Disease Prediction
This project explores the practical use of the application of Deep Learning in medical image diagnosis.
## Overview
This web application utilizes deep learning techniques to predict the likelihood of developing kidney disease. Built using Python, TensorFlow, Flask, MLflow, and DVC, the application provides a user-friendly interface for inputting patient data and receiving risk assessment results. An automated workflow seamlessly handles deployment and containerization, ensuring the application's accessibility and scalability.
## Features
The Fire Detection project offers the following features:
1. **Kidney Disease Prediction:**
2. **User-friendly Interface:**
## Demo
## Installation
To run this Fire Detection project locally, follow these steps:
1. Clone the Repository:
```bash
https://github.com/Msparihar/Kidney-Disease-Prediction.git
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
3. Run the App:
```bash
python main.py
```
## Contribution
Contributions to the Fire Detection project are welcome! If you'd like to contribute, please follow these steps:
1. Fork the repository on GitHub.
2. Create a new branch from the `main` branch.
3. Make your modifications and enhancements.
4. Test your changes thoroughly.
5. Commit and push your changes to your forked repository.
6. Submit a pull request to the main repository, describing your changes in detail.
Please ensure your contributions adhere to the project's coding standards and guidelines.
## Acknowledgments
The Fire Detection project is built upon various open-source libraries and resources. I would like to express my gratitude to the developers and contributors of the following projects:
- [Ultralytics](https://github.com/ultralytics/ultralytics)
- [Python](https://www.python.org/)
- [Flask](https://flask.palletsprojects.com/)
- [Roboflow](https://roboflow.com/)
- [MLFlow](https://mlflow.org/docs/latest/index.html)
## License
This project is licensed under the [MIT License](LICENSE). Feel free to modify and distribute it according to the terms of the license.
## Contact
If you have any questions, suggestions, or feedback regarding this project, please contact the project maintainer at manishsparihar2020@gmail.com
I really appreciate your interest in this project and hope you found this project helpful! Keep Exploring!