Abstract
Natural language processing systems (NLP) that extract clinical information from textual reports were shown to be effective for limited domains and for particular applications. Because an NLP system typically requires substantial resources to develop, it is beneficial if it is designed to be easily extendible to multiple domains and applications. This paper describes multiple extensions of an NLP system called MedLEE, which was originally developed for the domain of radiological reports of the chest, but has subsequently been extended to mammography, discharge summaries, all of radiology, electrocardiography, echocardiography, and pathology.
MeSH Terms
Decision Making, Computer-Assisted
Diagnostic Imaging
Humans
Natural Language Processing
Radiology
Vocabulary, Controlled
Authors & Affiliations
1 authors, click to expand affiliations / ORCID
Friedman C
Department of Computer Science, Queens College CUNY, USA.
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