Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES)

Architecture, component evaluation and applications

Guergana K. Savova, James J. Masanz, Philip V. Ogren, Jiaping Zheng, Sunghwan Sohn, Karin C. Kipper-Schuler, Christopher G. Chute

Research output: Contribution to journalArticle

691 Citations (Scopus)

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 accuracy=0.936; shallow parser F-score=0.924; named entity recognizer and system-level evaluation F-score=0.715 for exact and 0.824 for overlapping spans, and accuracy for concept mapping, negation, and status attributes for exact and overlapping spans of 0.957, 0.943, 0.859, and 0.580, 0.939, and 0.839, respectively. Overall performance is discussed against five applications. The cTAKES annotations are the foundation for methods and modules for higher-level semantic processing of clinical free-text.

Original languageEnglish (US)
Pages (from-to)507-513
Number of pages7
JournalJournal of the American Medical Informatics Association
Volume17
Issue number5
DOIs
StatePublished - Sep 1 2010

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Natural Language Processing
Semantics
Information Management
Electronic Health Records
Information Storage and Retrieval
Linguistics
Technology

ASJC Scopus subject areas

  • Health Informatics

Cite this

Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES) : Architecture, component evaluation and applications. / Savova, Guergana K.; Masanz, James J.; Ogren, Philip V.; Zheng, Jiaping; Sohn, Sunghwan; Kipper-Schuler, Karin C.; Chute, Christopher G.

In: Journal of the American Medical Informatics Association, Vol. 17, No. 5, 01.09.2010, p. 507-513.

Research output: Contribution to journalArticle

Savova, Guergana K. ; Masanz, James J. ; Ogren, Philip V. ; Zheng, Jiaping ; Sohn, Sunghwan ; Kipper-Schuler, Karin C. ; Chute, Christopher G. / Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES) : Architecture, component evaluation and applications. In: Journal of the American Medical Informatics Association. 2010 ; Vol. 17, No. 5. pp. 507-513.
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