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an advanced neural biomedical namedentity recognition and normalization tool


We present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by employing a multi-task NER model and neural network-based NEN models to achieve much faster and more accurate inference. This repository provides a way to host your own BERN2 server. See our paper for more details.

***** Try BERN2 at http://bern2.korea.ac.kr *****

Installing BERN2

You first need to install BERN2 and its dependencies.

# Install torch with conda (please check your CUDA version)
conda create -n bern2 python=3.7
conda activate bern2
conda install pytorch==1.9.0 cudatoolkit=10.2 -c pytorch
conda install faiss-gpu libfaiss-avx2 -c conda-forge

# Check if cuda is available
python -c "import torch;print(torch.cuda.is_available())"

# Install BERN2
git clone [email protected]:dmis-lab/BERN2.git
cd BERN2
pip install -r requirements.txt

(Optional) If you want to use mongodb as a caching database, you need to install and run it.

# https://docs.mongodb.com/manual/tutorial/install-mongodb-on-ubuntu/#install-mongodb-community-edition-using-deb-packages
sudo systemctl start mongod
sudo systemctl status mongod

Then, you need to download resources (e.g., external modules or dictionaries) for running BERN2. Note that you will need 70GB of free disk space.

wget http://nlp.dmis.korea.edu/projects/bern2/resources.tar.gz
tar -zxvf resources.tar.gz
rm -rf resources.tar.gz
# install CRF
cd resources/GNormPlusJava/CRF
./configure --prefix="$HOME"
make
make install
cd ../../..

Running BERN2

The following command runs BERN2.

export CUDA_VISIBLE_DEVICES=0
cd scripts
bash run_bern2.sh

(Optional) To restart BERN2, you need to run the following commands.

export CUDA_VISIBLE_DEVICES=0
cd scripts
bash stop_bern2.sh
bash start_bern2.sh

Annotations

Click here to download the annotations (NER and normalization) for 25.7+ millions of PubMed articles (From pubmed21n0001 to pubmed21n1057 (2021.01.12)) (Compressed, 18 GB).

The data provided by BERN2 is post-processed and may differ from the most current/accurate data available from U.S. National Library of Medicine (NLM).

Citation

@article{sung2022bern2,
    title={BERN2: an advanced neural biomedical namedentity recognition and normalization tool}, 
    author={Sung, Mujeen and Jeong, Minbyul and Choi, Yonghwa and Kim, Donghyeon and Lee, Jinhyuk and Kang, Jaewoo},
    year={2022},
    eprint={2201.02080},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

Contact Information

For help or issues using BERN2, please submit a GitHub issue. Please contact Mujeen Sung (mujeensung (at) korea.ac.kr), or Minbyul Jeong (minbyuljeong (at) korea.ac.kr) for communication related to BERN2.

GitHub

View Github


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