Automatic discovery of regular expression patterns representing negated findings in medical narrative reports

Roni Romano, Lior Rokach, Oded Maimon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Substantial medical data such as discharge summaries and operative reports are stored in textual form. Databases containing free-text clinical narratives reports often need to be retrieved to find relevant information for clinical and research purposes. Terms that appear in these documents tend to appear in different contexts. The context of negation, a negative finding, is of special importance, since many of the most frequently described findings are those denied by the patient or subsequently "ruled out." Hence, when searching free-text narratives for patients with a certain medical condition, if negation is not taken into account, many of the documents retrieved will be irrelevant. In this paper we examine the applicability of a new pattern learning method for automatic identification of negative context in clinical narratives reports. We compare the new algorithm to previous methods proposed for the same task of similar medical narratives and show its advantages. The new algorithm can be applied also to further context identification and information extraction tasks.

Original languageEnglish
Title of host publicationNext Generation Information Technologies and Systems - 6th International Conference, NGITS 2006, Proceedings
PublisherSpringer Verlag
Pages300-311
Number of pages12
ISBN (Print)3540354727, 9783540354727
DOIs
StatePublished - 2006
Event6th International Conference on Next Generation Information Technologies and Systems, NGITS 2006 - Kibbutz Shefayim, Israel
Duration: 4 Jul 20066 Jul 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4032 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Next Generation Information Technologies and Systems, NGITS 2006
Country/TerritoryIsrael
CityKibbutz Shefayim
Period4/07/066/07/06

Keywords

  • Information Retrieval
  • Machine Learning
  • Medical Informatics
  • Text Classification

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