Using NLP to extract concepts from chief complaints.

Michael Lieberman, Thomas N. Ricciardi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The NLM's MMTx natural language processing (NLP) engine was used to extract concepts from chief complaints entered into an ambulatory electronic medical record (EMR). Of the over 600,000 strings submitted to the process, approximately 25% were assigned at least one concept, with a rate of 2% for incorrect assignments.

Original languageEnglish (US)
Pages (from-to)1029
Number of pages1
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2005

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Natural Language Processing
Electronic Health Records

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Using NLP to extract concepts from chief complaints. / Lieberman, Michael; Ricciardi, Thomas N.

In: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2005, p. 1029.

Research output: Contribution to journalArticle

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