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HNC-PREDICTOR (Head and Neck Cancer Predictive Risk Estimator to Determine Control and Therapeutic Outcomes of Radiotherapy )

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uic-evl/hnc-predictor

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Interface

Prototype

Getting Started With The Frontend

In the project folder run

npm install

then run

npm start

Backend Configuration

Install R globally Install R packages - r-prodlim, r-pec

python venv

  1. Go to api folder

  2. Create a virtual environment (if not created already) python -m venv venv

  3. Activate the virtual environment (windows) .\venv\Scripts\activate (ubuntu) source venv/bin/activate

  4. Install dependencies from requirements.txt pip install -r requirements.txt

  5. set up flask app set FLASK_APP=backend.py

  6. run flask flask run

  7. if new dependencies are added, update requirements.txt pip freeze > requirements.txt

Alternate Python Backend Guide with anaconda

Python version <3.8 for rpy2

Create an ancaonda environment :

conda create -n lancet

Activate the environment:

conda activate lancet

Install necessary packages : c Install R globally

  1. Install Flask -

conda install -c anaconda flask

  1. Install Flask_CORS -

conda install -c anaconda flask-cors

  1. Install Pandas -

conda install -c anaconda pandas

  1. Insall Numpy -

conda install -c anaconda numpy

  1. Install rpy2 -

conda install -c r rpy2

  1. Install r-prodlim -

conda install -c conda-forge r-prodlim

  1. Install r-pec -

conda install -c conda-forge r-pec

Navigate to api folder then run

python backend.py

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