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A Novel Hybrid Approach to Automated Negation Detection in Clinical Radiology Reports
Author(s) -
Yang Huang,
Henry Lowe
Publication year - 2007
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1197/jamia.m2284
Subject(s) - negation , parsing , natural language processing , computer science , matching (statistics) , artificial intelligence , search engine indexing , information retrieval , programming language , medicine , pathology
Negation is common in clinical documents and is an important source of poor precision in automated indexing systems. Previous research has shown that negated terms may be difficult to identify if the words implying negations (negation signals) are more than a few words away from them. We describe a novel hybrid approach, combining regular expression matching with grammatical parsing, to address the above limitation in automatically detecting negations in clinical radiology reports.

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