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TuringCare - Lung Disease Management Application

TuringCare is an academic project developed in the framework of AI studies at ESPRIT by TuringTeam

Initial Release v1.0

TuringCare enables fast and effective disease response by providing an easy management and access to patient information at one place. The TuringCare web app also allows healthcare professionals to early detect lung diseases (Covid-19, Tuberculosis, Viral Pneumonia) in Chest X-Ray images and link results to patients' records. The TuringCare app uses Artificial Intelligence to classify diseases and interpret abnormalities in the lungs from Chest X-Ray images.

Features

Account & Authentification
  • Register an account.
  • Log in into an account.
  • Update account informations.
Patients Management
  • Create a new patient.
  • View a patient record (general information, related model prediction results).
  • View all patients.
  • Update a patient.
  • Delete a patient.
Predictions Management
  • Import and classify a Chest X-Ray image using CNN deep learning model.
  • View prediction results.
  • View all predictions.
  • Update a prediction (link Chest X-Ray to a patient, enter feedback).
  • Delete a prediction.

Tech

TuringCare uses open source projects and frameworks to work properly:

  • Django - a python-based free and open-source web framework.
  • Bootstrap 5 - a free and open-source CSS framework directed at responsive, mobile-first front-end web development.
  • TensorFlow - a free and open-source software library for machine learning and artificial intelligence.
  • Volt Django Dashboard - a free and open source Django Dashboard Template.

And of course TuringCare itself is open source with a public repository on GitHub.

Installation

Step 1: Install tools

  • Git
  • NodeJS 12.x or higher
  • Gulp - globally
    • npm install -g gulp-cli

Step 2: Clone Repo

git clone https://github.com/abdessalemmami/turing-care-app.git

Step 3: Install Node Modules

cd apps/static/assets
npm install

Step 4: Edit & Recompile SCSS files

gulp scss

Step 5: Configure Virtual Environment

cd turing-care-app
pip install virtualenv
virtualenv env
.\env\Scripts\activate
pip3 install -r requirements.txt

Step 6: Create Database Tables

python manage.py makemigrations
python manage.py migrate

Step 7: Run Development Server

python manage.py runserver

Access the web app in your preferred browser (http://127.0.0.1:8000/) and that's it!

Team

License

MIT

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