AI Article Synopsis
- The growth of Natural Language Processing (NLP) tools for clinical free-text has led to challenges in interoperability between different systems, despite frameworks meant to allow for component integration.
- The Open Health Natural Language Processing (OHNLP) Consortium fosters collaboration in clinical NLP by offering UIMA-based open source software and maintaining a catalog of related tools to aid system interactions.
- Apache cTAKES focuses on incorporating high-quality annotators to create an advanced NLP system that can effectively access clinical information, complementing OHNLP's efforts to link research with practical health technology.
Article Abstract
The number of Natural Language Processing (NLP) tools and systems for processing clinical free-text has grown as interest and processing capability have surged. Unfortunately any two systems typically cannot simply interoperate, even when both are built upon a framework designed to facilitate the creation of pluggable components. We present two ongoing activities promoting open source clinical NLP. The Open Health Natural Language Processing (OHNLP) Consortium was originally founded to foster a collaborative community around clinical NLP, releasing UIMA-based open source software. OHNLP's mission currently includes maintaining a catalog of clinical NLP software and providing interfaces to simplify the interaction of NLP systems. Meanwhile, Apache cTAKES aims to integrate best-of-breed annotators, providing a world-class NLP system for accessing clinical information within free-text. These two activities are complementary. OHNLP promotes open source clinical NLP activities in the research community and Apache cTAKES bridges research to the health information technology (HIT) practice.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419764 | PMC |
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