An Automated NLP Tool to Rank Applications for Diagnostic Radiology Residency: Utility for Understanding Elements Associated with Selection for Interview
This is the code repository for the paper: An Automated NLP Tool to Rank Applications for Diagnostic Radiology Residency: Utility for Understanding Elements Associated with Selection for Interview
We developed a web system application for users to test our proposed pipilne for ranking Applications for Diagnostic Radiology Residency. An example of our Web System is illustraded bellow:
We recommend using a virtual environment
If you do not already have conda
installed, you can install Miniconda from this link (~450Mb). Then, check that conda is up to date:
conda update -n base -c defaults conda
And create a fresh conda environment (~220Mb):
conda create python=3.8 --name=nlp_ranking
If not already activated, activate the new conda environment using:
conda activate nlp_ranking
Then install the following packages (~3Gb):
conda install pytorch cudatoolkit=10.2 -c pytorch
conda install pytorch torchvision torchaudio -c pytorch
pip3 install -r requirements.txt
wget https://raw.githubusercontent.com/chenrui333/homebrew-core/0094d1513ce9e2e85e07443b8b5930ad298aad91/Formula/libomp.rb
brew unlink libomp
brew install --build-from-source ./libomp.rb
brew list --version libomp
python3 app/src/download_models.py
A minimal demo app is provided for you to play with the classification model!
You can easily run your app in your default browser by running:
cd src
python3 app.py >/dev/null 2>&1
Ms. Thiago Santos
Rishav Dhar
Dr. Amara Tariq
Dr. Imon Banerjee