The accuracy of using integrated electronic health care data to identify patients with undiagnosed diabetes mellitus.
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Design patterns for the development of electronic health record-driven phenotype extraction algorithms.Relational machine learning for electronic health record-driven phenotyping.Distinguishing incident and prevalent diabetes in an electronic medical records databaseA rule-based electronic phenotyping algorithm for detecting clinically relevant cardiovascular disease casesAssessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.A machine learning-based framework to identify type 2 diabetes through electronic health records.Are users of sulphonylureas at the time of an acute coronary syndrome at risk of poorer outcomes?
P2860
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P2860
The accuracy of using integrated electronic health care data to identify patients with undiagnosed diabetes mellitus.
description
2011 nî lūn-bûn
@nan
2011 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
The accuracy of using integrat ...... undiagnosed diabetes mellitus.
@ast
The accuracy of using integrat ...... undiagnosed diabetes mellitus.
@en
type
label
The accuracy of using integrat ...... undiagnosed diabetes mellitus.
@ast
The accuracy of using integrat ...... undiagnosed diabetes mellitus.
@en
prefLabel
The accuracy of using integrat ...... undiagnosed diabetes mellitus.
@ast
The accuracy of using integrat ...... undiagnosed diabetes mellitus.
@en
P2093
P2860
P1476
The accuracy of using integrat ...... undiagnosed diabetes mellitus.
@en
P2093
Alan J Forster
Doug Manuel
Erin Keely
Janine Malcolm
Michael L Ho
Nadine Lawrence
Robert D Reid
P2860
P304
P356
10.1111/J.1365-2753.2011.01633.X
P577
2011-02-17T00:00:00Z