A de-identification toolkit for clinical text in Hebrew.
To install the package, clone the repo and install all dependencies, preferably in a virtual environment:
# Create conda env (optional)
conda create --name hebsafeharbor python=3.8
conda activate hebsafeharbor
# Install dependencies
pip install -r requirements.txt
# (Optional) Install package locally
pip install -e .
# Download the he_ner_news_trf model used by hebsafeharbor
pip install https://github.com/8400TheHealthNetwork/HebSpacy/releases/download/he_ner_news_trf-3.2.1/he_ner_news_trf-3.2.1-py3-none-any.whlfrom hebsafeharbor import HebSafeHarbor
hsh = HebSafeHarbor()
text = """שרון לוי התאשפזה ב02.02.2012 וגרה בארלוזרוב 16 רמת גן"""
doc = {"text": text}
output = hsh([doc])
print(output)- Run the following command to install and run the server and demo services:
docker-compose up -d --build- Navigate in the browser http://localhost:8080/docs to test the Server swagger
- Navigate in the browser http://localhost:8501 to test the Demo app