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Healthcare Application leveraging modern technologies for improved patient care. Features include patient management, appointment scheduling, and various health condition predictions using machine learning models. This project utilizes datasets for cancer, diabetes, heart, liver, kidney, malaria, and pneumonia predictions.

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zeeza18/Healthcare-Application

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Healthcare Application

This is a Healthcare Application designed to improve patient care by leveraging modern technologies. The application includes features for patient management, appointment scheduling, and more.

Table of Contents

  1. Getting Started
  2. Prerequisites
  3. Installation
  4. Running the Application
  5. Datasets
  6. Acknowledgements
  7. License

Getting Started

Follow these instructions to get a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

  • Python 3.7 or higher
  • Git

Installation

  1. Clone the repository:

    git clone https://github.com/zeeza18/Healthcare-Application.git
    cd Healthcare-Application
    
  2. Create a virtual environment:

    python3 -m venv venv
    
  3. Activate the virtual environment:

    • On Windows:

      .\\venv\\Scripts\\activate
      
    • On MacOS/Linux:

      source venv/bin/activate
      
  4. Install the required libraries:

    pip install -r requirements.txt
    

Running the Application

  1. Set environment variables (if any):

    Make sure to set any required environment variables. For example:

    export FLASK_APP=app.py
    export FLASK_ENV=development   
    
  2. Run the Flask application:

    flask run
    
    The application will be available at \`http://127.0.0.1:5000/\`.
    

Datasets

Kernels used for training deep learning models:

Details of various datasets used for model development:

Application Images

home

about

Diseases Panel

checker

Acknowledgements

We would like to acknowledge Krish Naik for his invaluable guidance and contributions to this project.

License

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

All datasets used in this project are licensed under their respective licenses. Please refer to the datasets' documentation for more information.

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Healthcare Application leveraging modern technologies for improved patient care. Features include patient management, appointment scheduling, and various health condition predictions using machine learning models. This project utilizes datasets for cancer, diabetes, heart, liver, kidney, malaria, and pneumonia predictions.

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