- Written by Wei-Hung Weng (HMS, MGH)
- Created: Nov 9, 2016
- Latest update: Nov 27, 2017
- Please contact the author with errors found.
- ckbjimmy {AT} mit {DOT} edu
git clone
the repositorypython setup.py install
- Go to the directory
- Run
sh test_model.sh
- Download fasttext embedding from fasttext website (Use either
wiki-news-300d-1M.vec
orwiki-news-300d-1M-subword.vec
, depends on your text) - use
python EmbCRNN.py [text_path] [label_path] [embedding_path]
- use
python Doc2vec.py [text_path] [label_path]
If you use this code, please kindly cite the paper for this GitHub project (see below for BibTex):
@article{weng2017medical,
title = {Medical Subdomain Classification of Clinical Notes Using a Machine Learning-Based Natural Language Processing Approach.},
author = {Weng, Wei-Hung and Wagholikar, Kavishwar B. and McCray, Alexa T. and Szolovits, Peter and Chueh, Henry C.},
journal = {BMC Medical Informatics and Decision Making.},
year = {2017},
number = {17},
page = {155},
note = {\mbox{doi}:\url{10.1186/s12911-017-0556-8}}
}
The code belongs to Wei-Hung Weng and Laboratory of Computer Science, Massachusetts General Hospital.