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Open Source Clinical NLP – More than Any Single System

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 cr...

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Detalles Bibliográficos
Autores principales: Masanz, James, Pakhomov, Serguei V., Xu, Hua, Wu, Stephen T., Chute, Christopher G., Liu, Hongfang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419764/
https://www.ncbi.nlm.nih.gov/pubmed/25954581
Descripción
Sumario: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.