A parser designed for free text clinical trial eligibility criteria (CTEC).
Parsing free text CTEC and formalizing into OMOP CDM v5 table
The parser was trained on 250 clinical trials on Alzheimer's. The annotation guidelines is in folder Supple Materials.
Developed in Dr. Chunhua Weng's lab in Department of Biomedical Informatics at Columbia
Author: Tian Kang
Affiliation: Department of Biomedical Informatics, Columbia University
Contact Email: email@example.com
Last update: June 20, 2016 (add Negation detection in NER step)
Citation:EliIE: An open-source information extraction system for clinical trial eligibility criteria
First download all codes and decompress
sh wrapper_for_parsing.sh" and parsing results will be generated in XML files.
sh wrapper_for_parsing.sh" without changing )
python NamedEntityRecognition.py $1:<input directory> $2:<input text name> $3:<output directory>
python Relation.py $3:<output directory> $2:<input text name>
python NamedEntityRecognition.py Tempfile test.txt Tempfile
python Relation.py Tempfile test.txt
This parser assumes MetaMap is installed and requires that the MetaMap support services are running. If you have MetaMap installed in
$MM, these can be started as:
features_dir and open
metamap_tag.sh; follow the guidance to change the MetaMap root dir and start running
Easy installation following the instruction: