This is an implementation of our paper "KART: Parameterization of Privacy Leakage Scenarios from Pre-trained Language Models."
- Python 3.6.4
- Make sure that
$HOME
is set to environment variable$PYTHONPATH
.
We simulate privacy leakage from clinical records using MIMIC-III-dummy-PHI.
MIMIC-III-dummy-PHI is made by embedding pieced of dummy protected health information (PHI) in MIMIC-III corpus.
To install using venv
module, use the following commands:
# Clone Repository
cd ~
git clone [email protected]:yutanakamura-tky/kart.git
cd ~/kart
# Install dependencies
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
To install using Poetry, use the following commands:
# Install Poetry
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py > ~/get-poetry.py
cd ~
python get-poetry.py --version 1.1.4
poetry config virtualenvs.in-project true
# Clone Repository
cd ~
git clone [email protected]:yutanakamura-tky/kart.git
cd ~/kart
# Activate virtual environment & install dependencies
poetry shell
poetry install
This repository requires two datasets to create MIMIC-III-dummy-PHI:
- MIMIC-III version 1.4 noteevents (
NOTEEVENTS.csv.gz
) (here) - n2c2 2006 De-identification challenge training dataset "Data Set 1B: De-identification Training Set" (
deid_surrogate_train_all_version2.zip
) (here)
Note that registration is necessary to download these datasets.
After downloading the datasets, extract them into ~/kart/corpus
:
mv /path/to/NOTEEVENTS.csv.gz ~/kart/corpus
cd ~/kart/corpus
gunzip NOTEEVENTS.csv.gz
mv /path/to/deid_surrogate_train_all_version2.zip ~/kart/corpus
cd ~/kart/corpus
unzip deid_surrogate_train_all_version2.zip
Run make_mimic_iii_dummy_phi.sh
. Make sure that you are in the virtual environment:
cd ~/kart/src
bash make_mimic_iii_dummy_phi.sh
cd ~/kart/src
bash make_pretraining_data.sh
To pre-train BERT model from scratch, use this command:
cd ~/kart/src
bash pretrain_bert_from_scratch.sh
To pre-train BERT model from BERT-base-uncased model, use this command:
cd ~/kart/src
# Download BERT-base-uncased model by Google Research
bash get_google_bert_model.sh
bash pretrain_bert_from_bert_base_uncased.sh
Please cite our arXiv preprint:
@misc{kart,
Author = {Yuta Nakamura and Shouhei Hanaoka and Yukihiro Nomura and Naoto Hayashi and Osamu Abe and Shuntaro Yada and Shoko Wakamiya and Eiji Aramaki},
Title = {KART: Parameterization of Privacy Leakage Scenarios from Pre-trained Language Models},
Year = {2020},
Eprint = {arXiv:2101.00036},
}