Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural language processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed.
%0 Journal Article
%1 DemnerFushman:2009
%A Demner-Fushman, Dina
%A Chapman, Wendy W.
%A McDonald, Clement J.
%D 2009
%J Journal of Biomedical Informatics
%K biomedical NLP
%T What Can Natural Language Processing Do for Clinical Decision Support?
%X Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural language processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed.
@article{DemnerFushman:2009,
abstract = {Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural language processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed.},
added-at = {2009-08-28T21:54:11.000+0200},
author = {Demner-Fushman, Dina and Chapman, Wendy W. and McDonald, Clement J.},
biburl = {https://www.bibsonomy.org/bibtex/270a3dbc9b4267af21c93d25ad6042dfb/diego_ma},
interhash = {0d6b01964a41eee6a62674c8fe842a86},
intrahash = {70a3dbc9b4267af21c93d25ad6042dfb},
journal = {Journal of Biomedical Informatics},
keywords = {biomedical NLP},
note = {Online uncorrected proof},
timestamp = {2009-08-28T21:54:11.000+0200},
title = {What Can Natural Language Processing Do for Clinical Decision Support?},
year = 2009
}