Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study.
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%0 Journal Article
%1 journals/jbi/AndersonKTLXC16
%A Anderson, Ariana E.
%A Kerr, Wesley T.
%A Thames, April
%A Li, Tong
%A Xiao, Jiayang
%A Cohen, Mark S.
%D 2016
%J J. Biomed. Informatics
%K
%P 162-168
%T Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study.
%U http://dblp.uni-trier.de/db/journals/jbi/jbi60.html#AndersonKTLXC16
%V 60
@article{journals/jbi/AndersonKTLXC16,
added-at = {2023-12-12T21:11:41.000+0100},
author = {Anderson, Ariana E. and Kerr, Wesley T. and Thames, April and Li, Tong and Xiao, Jiayang and Cohen, Mark S.},
biburl = {https://www.bibsonomy.org/bibtex/25528f0781b9437d90282f5d4c39d3fd3/admin},
ee = {https://www.wikidata.org/entity/Q40168490},
interhash = {3a8438c250fb7d45738e36bcbd5db903},
intrahash = {5528f0781b9437d90282f5d4c39d3fd3},
journal = {J. Biomed. Informatics},
keywords = {},
pages = {162-168},
timestamp = {2023-12-12T21:11:41.000+0100},
title = {Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study.},
url = {http://dblp.uni-trier.de/db/journals/jbi/jbi60.html#AndersonKTLXC16},
volume = 60,
year = 2016
}
