hebsafeharbor 0.0.2

De-identification toolkit for clinical text in Hebrew

HebSafeHarbor

A de-identification toolkit for clinical text in Hebrew.

Installation

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.whl

Getting started

Python

from 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)

Docker

1. Run the following command to install and run the server and demo services:

docker-compose up -d --build

2. Navigate in the browser http://localhost:8080/docs to test the Server swagger
3. Navigate in the browser http://localhost:8501 to test the Demo app