Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications

Mayo Clinic in Florida · Mayo Clinic · +1 more institution

PubMed
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Abstract

We aim to build and evaluate an open-source natural language processing system for information extraction from electronic medical record clinical free-text. We describe and evaluate our system, the clinical Text Analysis and Knowledge Extraction System (cTAKES), released open-source at http://www.ohnlp.org. The cTAKES builds on existing open-source technologies-the Unstructured Information Management Architecture framework and OpenNLP natural language processing toolkit. Its components, specifically trained for the clinical domain, create rich linguistic and semantic annotations. Performance of individual components: sentence boundary detector accuracy=0.949; tokenizer accuracy=0.949; part-of-speech tagger…

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Authors

7

Topics & keywords

Keywords
  • Computer science
  • Natural language processing
  • Parsing
  • Information extraction
  • Component (thermodynamics)
  • Artificial intelligence
  • Sentence
  • Biomedical text mining
UN Sustainable Development Goals
  • Quality Education
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