A project for 2020 PKU Computer Network. We build a new way to manage patients and clinical records. A neural network prediction model is added to help you quickly identify COVID-19 carriers.

This project is based on Flask + Pytorch + Nginx + Gunicorn + Docker.

We have deployed this project here.

Here we explain the core documents in our project.

• app : The Flask APP
  app
  ├── __init__.py : initialize Flask app
  ├── email.py : send the reset password email
  ├── errors.py : handle 404 and 505 errors
  ├── evaluator : the neural network prediction model
  ├── forms.py : define the forms
  ├── models.py : define the classes used in database
  ├── routes.py : routers, implement functions for different URLs
  ├── static : static resources used by HTML templates
  ├── templates : html templates and mail templates
  └── utils.py : assisting functions for routers

• config.py : The parameters used in this project

• requirements.txt : The package requirements in this project

• method: get, post
  url: '/' or '/index'
  return: render_template("home.html")
  description: render homepage

• method: get, post
  url: '/login'
  return: render_template('login.html')
  description: login

• method: get
  url: '/logout'
  return: redirect(url_for('index'))
  description: logout

• method: get, post
  url: '/register'
  return: render_template('register.html')
  description: register a new user

• method: get
  url: '/user/<username>'
  return: render_template('user.html')
  description: display a user's profile

• method: get, post
  url: '/edit_profile'
  return: render_template('edit_profile.html')
  description: edit a user's profile

• method: get, post
  url: '/reset_password_request'
  return: render_template('reset_password_request.html')
  description: send reset password request mail

• method: get, post
  url: '/reset_password/<token>'
  return: render_template('reset_password.html')
  description: reset password, token is used for encryption, it only remains valid for 5 minutes

• method: get, post
  url: '/patient_profile/<int: unit_id>'
  return: render_template("patient_profile.html")
  description: render patient profile, and add clinical record for the patient

• method: get, post
  url: '/dashboards'
  return: render_template("dashboards.html")
  description: send the contents in database to HTML, display the contents in database

• method: get url: '/record/manage'
  return: render_template("manage_record.html")
  description: display clinical records in database

• method: get, post
  url: '/record/add'
  return: render_template("add_record.html")
  description: add clinical record to database

• method: post
  url: '/record/<int:record_id>/delete'
  return: redirect_back()
  description: delete a clinical record with ID = record_id

• method: get, post
  url: '/record/<int:record_id>/edit'
  return: render_template("edit_record.html")
  description: edit a clinical record that already exists in database, redirect back to the last page after editing operation

• method: get, post
  url: '/unit/add'
  return: render_template("add_unit.html")
  description: add a new patient to database and redirect back to the last page

• method: get url: '/unit/manage'
  return: render_template("manage_unit.html")
  description: display patients in database

• method: post
  url: '/unit/<int:unit_id>/delete'
  return: redirect_back()
  description: delete a patient with ID = unit_id

• method: get, post
  url: '/unit/<int:unit_id>/edit' return: render_template("edit_unit.html")
  description: edit a patient's profile, redirect back to the last page after done

• method: get
  url: '/unit/<int:unit_id>/settings/avatar'
  return: render_template("change_avatar.html")
  description: change avatar for a patient, redirect back after done

• method: post
  url: '/unit/<int:unit_id>/settings/avatar/upload'
  return: redirect(url_for('change_avatar', unit_id=unit.id))
  description: upload avatar to database

• method: post
  url: '/unit/<int:unit_id>/settings/avatar/crop'
  return: redirect(url_for('change_avatar', unit_id=unit.id))
  description: crop avatar in database

• method: get
  url: '/avatars/<path:filename>'
  return: send_from_directory(app.config['AVATARS_SAVE_PATH'], filename)
  description: get avatar in database

• method: get, post
  url: '/quick_evaluation'
  return: render_template('quick_evaluation.html')
  description: display the evaluation records in database

• method: get, post
  url: '/add_evaluation'
  return: render_template('add_evaluation.html')
  description: add a new evaluation to database

• method: post
  url: '/delete_evaluation/<int:evaluation_id>'
  return: redirect_back()
  description: delete a evaluation record with ID = evaluation_id in database

We first show how to deploy our project using Docker.

We also provide a version without Docker.

1. Install Docker.

   #Uninstall old versions
   sudo apt-get remove docker docker-engine docker.io containerd runc
   #Setup the repository
   sudo apt-get update
   
   sudo apt-get install \
       apt-transport-https \
       ca-certificates \
       curl \
       gnupg-agent \
       software-properties-common
   #Add Docker's official GPG key
   curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
   #Install Docker Engine
   sudo apt update
   sudo apt install docker-ce docker-ce-cli containerd.io

   Refer Docker's official website for more details.

2. Download image from Docker Hub.

   docker pull primavera/compnet

1. Create a container from the image.

docker run -it -p 80:80 --name new_compnet primavera/compnet

2. Enter the directory.

cd /deploy/compNet/

3. Start Nginx.

service nginx start

4. Start Gunicorn.

gunicorn -w 4 -b 127.0.0.1:8000 app:app

See file requirements.txt

1. Install virtualenv.

pip3 install virtualenv

2. Install dependence.

pip3 install -r requirements.txt

3. Install Pytorch.

Select a proper version of Pytorch on this website.

3. Setup Nginx.

Replace default.conf in /etc/nginx/sites-enabled/ by compNet.conf.

mv ./compNet.conf /etc/nginx/sites-enabled/

5. Activate virtual environment.

source ./venv/bin/activate

6. Start Gunicorn.

gunicorn -w 4 -b 127.0.0.1:8000 app:app

Here shows some operations of our project.

• login with username and password
• add and view a patient
• add and view a record
• add and view a COVID-19 test
• view statistics of all COVID-19 tests