Identifying important concepts from medical documents
Document Type
Article
Publication Date
12-1-2006
Abstract
Automated medical concept recognition is important for medical informatics such as medical document retrieval and text mining research. In this paper, we present a software tool called keyphrase identification program (KIP) for identifying topical concepts from medical documents. KIP combines two functions: noun phrase extraction and keyphrase identification. The former automatically extracts noun phrases from medical literature as keyphrase candidates. The latter assigns weights to extracted noun phrases for a medical document based on how important they are to that document and how domain specific they are in the medical domain. The experimental results show that our noun phrase extractor is effective in identifying noun phrases from medical documents, so is the keyphrase extractor in identifying important medical conceptual terms. They both performed better than the systems they were compared to. © 2006 Elsevier Inc. All rights reserved.
Identifier
33750840050 (Scopus)
Publication Title
Journal of Biomedical Informatics
External Full Text Location
https://doi.org/10.1016/j.jbi.2006.02.001
ISSN
15320464
PubMed ID
16545986
First Page
668
Last Page
679
Issue
6
Volume
39
Grant
DUE-0226075
Fund Ref
National Science Foundation
Recommended Citation
Li, Quanzhi and Wu, Yi Fang Brook, "Identifying important concepts from medical documents" (2006). Faculty Publications. 18554.
https://digitalcommons.njit.edu/fac_pubs/18554
