A Django-based Web Application Implementing Modified Gale Shapley Algorithm in the Medical Context of Patient - Donor Exchanges.
The idea here is that the institution has the list of available donors and their associated data available at all times, and patient accounts are accessed to request the transplants keeping in mind the various constraints of medical procedures.
You just need Python 3.6 or above to run this flawlessly.
For a one stop solution, I always use conda. First install conda and create you own environment as:
conda create --name myenv
where myenv is the environment name (which can be changed at will). Then activate the environment by:
source activate myenv
and then install Python using a single command:
conda install -c conda-forge python
You can execute the project using the following command in the src folder:
python manage.py runserver
Since I had no prior experience in web-based designing, I had to rely on a few open source implementations for making the project aesthetically pleasing. Thanks to everyone whose designs helped me in reaching over to a final product. A special shout-out to Srajan Garg and his team's work using CSS and Materialize that helped me in the beautification of the idea implemented above. The core design also helped me in coming up with a rather novel way of representing the data and the algorithm involved.