Classification of medication status change in clinical narratives

Sunghwan Sohn, Sean P. Murphy, James J. Masanz, Jean-Pierre Kocher, Guergana K. Savova

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The patient's medication history and status changes play essential roles in medical treatment. A notable amount of medication status information typically resides in unstructured clinical narratives that require a sophisticated approach to automated classification. In this paper, we investigated rule-based and machine learning methods of medication status change classification from clinical free text. We also examined the impact of balancing training data in machine learning classification when using the data from skewed class distribution.

Original languageEnglish (US)
Pages (from-to)762-766
Number of pages5
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Volume2010
StatePublished - 2010

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Machine Learning
Therapeutics

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Classification of medication status change in clinical narratives. / Sohn, Sunghwan; Murphy, Sean P.; Masanz, James J.; Kocher, Jean-Pierre; Savova, Guergana K.

In: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, Vol. 2010, 2010, p. 762-766.

Research output: Contribution to journalArticle

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