This code has been validated using the included notebooks on Python v 3.7.2. Python 2.x is no longer supported.
pyConTextNLP is a Python implementation/extension/modification of the ConText algorithm described in CITE which is itself a generalization of the NegEx algorithm described in CITE.
The package is maintained by Brian Chapman at the University of Utah. Other active and past developers include:
- Wendy W. Chapman
- Glenn Dayton
- Danielle Mowery
MAASTRO docker-version (maastrodocker/pycontextnlp) -------------This fork of pyContextNLP adds docker and TCP support, documentation can be found here
pyConTextNLP is a partial implementation of the ConText algorithm using Python. The original description of pyConTextNLP was provided in Chapman BE, Lee S, Kang HP, Chapman WW, "Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm." J Biomed Inform. 2011 Oct;44(5):728-37
Other publications/presentations based on pyConText include: * Wilson RA, et al. "Automated ancillary cancer history classification for mesothelioma patients from free-text clinical reports." J Pathol Inform. 2010 Oct 11;1:24. * Chapman BE, Lee S, Kang HP, Chapman WW. "Using ConText to Identify Candidate Pulmonary Embolism Subjects Based on Dictated Radiology Reports." (Presented at AMIA Clinical Research Informatics Summit 2011) * Wilson RA, Chapman WW, DeFries SJ, Becich MJ, Chapman BE. "Identifying History of Ancillary Cancers in Mesothelioma Patients from Free-Text Clinical Reports." (Presented at AMIA 2010).
Note: we changed the package name from pyConText to pyConTextNLP because of a name conflict on pypi.
The latest version of pyConTextNLP is available on [github](https://github.com/chapmanbe/pyConTextNLP). The package can be installed by either cloning the repository and running python setup.py install. Alternatively or by .. code:: shell pip install git+https://github.com/chapmanbe/pyConTextNLP.git
pyConTextNLP is also available via the Python Package Index and can be installed via
pip install pyConTextNLPDependencies include
- networkx
- PyYAML
See the notebooks folder for a series of walkthroughs demonstrating pyConTextNLP core concepts with example data.
I am working on improving the documentation and (hopefully) adding some testing to the code.
Some preliminary comments:
- pyConTextNLP works marks up text on a sentence by sentence level.
- pyConTextNLP assumes the sentence is a string not a list of words
- Our preferred way to represent knowledge is now with YAML files rather than TSV files.