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        "author": "Yifan Peng",
        "author_email": "yifan.peng@nih.gov",
        "bugtrack_url": null,
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            "Intended Audience :: Science/Research",
            "License :: Public Domain",
            "Operating System :: MacOS",
            "Operating System :: POSIX",
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            "Programming Language :: Python",
            "Topic :: Software Development",
            "Topic :: Software Development :: Libraries :: Application Frameworks"
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        "description": ".. image:: https://github.com/yfpeng/negbio/blob/master/images/negbio.png?raw=true\n   :target: https://github.com/yfpeng/negbio/blob/master/images/negbio.png?raw=true\n   :alt: NegBio\n\n-----------------------\n\n.. image:: https://img.shields.io/travis/yfpeng/NegBio/master.svg\n   :target: https://travis-ci.org/yfpeng/NegBio\n   :alt: Build status\n\n.. image:: https://img.shields.io/pypi/v/negbio.svg\n   :target: https://pypi.python.org/pypi/negbio\n   :alt: PyPI version\n\n.. image:: https://img.shields.io/readthedocs/negbio.svg\n   :target: http://negbio.readthedocs.io\n   :alt: RTD version\n\n\n\nNegBio is a high-performance NLP tool for negation and uncertainty detection in clinical texts (e.g. radiology reports).\n\n\nGet started\n===========\n\nInstall NegBio\n~~~~~~~~~~~~~~\n\n1. Installing from source (recommended)\n\n    .. code-block:: bash\n\n         $ git clone https://github.com/ncbi-nlp/NegBio.git\n         $ cd /path/to/negbio\n         $ python setup.py install --user\n         $ export PATH=~/.local/bin:$PATH\n\n2. Installing from pip\n\n    .. code-block:: bash\n\n        $ pip install negbio\n\n\n\n\nPrepare the dataset\n~~~~~~~~~~~~~~~~~~~\n\nThe inputs can be in either plain text or `BioC <http://bioc.sourceforge.net/>`_ format.\nIf the reports are in plain text, each report needs to be in a single file.\nSome examples can be found in the ``examples`` folder.\n\nRun the script\n~~~~~~~~~~~~~~\n\nThere are two ways to run the pipeline.\n\n**NOTE**: If you want to process a lot of reports (e.g., > 1000), it is recommended to run the pipeline step-by-step.\nSee `User guide <https://negbio.readthedocs.io/en/latest/user_guide.html>`_.\n\n\nUsing the CheXpert algorithm\n____________________________\n\nIf you want to use the `CheXpert <https://github.com/stanfordmlgroup/chexpert-labeler>`_ method, run one of the following lines\n\n.. code-block:: bash\n\n   $ main_chexpert text --output=examples examples/00000086.txt examples/00019248.txt\n\n.. code-block:: bash\n\n   $ main_chexpert bioc --output=examples examples/1.xml\n\n\nUsing MetaMap\n_____________\n\nIf you want to use MetaMap, run the following command by replacing ``<METAMAP_BINARY>`` with the actual **ABSOLUTE**\npath, such as **META_MAP_HOME/bin/metamap16**\n\n.. code-block:: bash\n\n   $ main_mm text --metamap=<METAMAP_BINARY> --output=examples examples/00000086.txt \\\n        examples/00019248.txt\n\n.. code-block:: bash\n\n   $ main_mm bioc --metamap=<METAMAP_BINARY> --output=examples examples/1.xml\n\n\nDocumentation\n=============\n\nnegbio `documentation <http://negbio.readthedocs.io/en/latest/>`_ is available on Read The Docs.\n\nSee `Getting Started <http://negbio.readthedocs.io/en/latest/getting_started.html>`_ for installation and basic\ninformation. To contribute to negbio, read our `contribution guide </CONTRIBUTING.md>`_.\n\nCiting NegBio\n=============\n\nIf you're running the NegBio pipeline, please cite:\n\n*  Peng Y, Wang X, Lu L, Bagheri M, Summers RM, Lu Z. `NegBio: a high-performance tool for negation and uncertainty\n   detection in radiology reports <https://arxiv.org/abs/1712.05898>`_. *AMIA 2018 Informatics Summit*. 2018.\n*  Wang X, Peng Y, Lu L, Bagheri M, Lu Z, Summers R. `ChestX-ray8: Hospital-scale Chest X-ray database and benchmarks\n   on weakly-supervised classification and localization of common thorax diseases <https://arxiv.org/abs/1705.02315>`_.\n   *IEEE Conference on Computer Vision and Pattern Recognition (CVPR)*. 2017, 2097-2106.\n\nAcknowledgments\n===============\n\nThis work was supported by the Intramural Research Programs of the National Institutes of Health, National Library of\nMedicine and Clinical Center.\n\nWe are grateful to the authors of NegEx, MetaMap, Stanford CoreNLP, Bllip parser, and CheXpert labeler for making\ntheir software tools publicly available.\n\nWe thank Dr. Alexis Allot for the helpful discussion.\n\nDisclaimer\n==========\nThis tool shows the results of research conducted in the Computational Biology Branch, NCBI. The information produced\non this website is not intended for direct diagnostic use or medical decision-making without review and oversight\nby a clinical professional. Individuals should not change their health behavior solely on the basis of information\nproduced on this website. NIH does not independently verify the validity or utility of the information produced\nby this tool. If you have questions about the information produced on this website, please see a health care\nprofessional. More information about NCBI's disclaimer policy is available.",
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