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.

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:

     https://github.com/Msparihar/Kidney-Disease-Prediction.git

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the App:

   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
• Python
• Flask
• Roboflow
• MLFlow

License

This project is licensed under the MIT 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 [e-mail]

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I really appreciate your interest in this project and hope you found this project helpful! Keep Exploring!