Covariate balance between the 2 Alzheimer’s disease phenotype algorithms.

Covariate balance between the 2 Alzheimer’s disease phenotype algorithms.

<p>Covariate balance between the 2 Alzheimer’s disease phenotype algorithms.</p>

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Bibliographic Details
Main Author:	Gowtham A. Rao (8261928) (author)
Other Authors:	Azza Shoaibi (506376) (author), Rupa Makadia (829197) (author), Jill Hardin (194317) (author), Joel Swerdel (20570864) (author), James Weaver (529211) (author), Erica A. Voss (8261922) (author), Mitchell M. Conover (13789186) (author), Stephen Fortin (13006809) (author), Anthony G. Sena (4899040) (author), Chris Knoll (4814352) (author), Nigel Hughes (5744633) (author), James P. Gilbert (8299149) (author), Clair Blacketer (12076668) (author), Alan Andryc (20570867) (author), Frank DeFalco (8766510) (author), Anthony Molinaro (12994931) (author), Jenna Reps (586831) (author), Martijn J. Schuemie (12641362) (author), Patrick B. Ryan (3321690) (author)
Published:	2025
Subjects:	Medicine Genetics Molecular Biology Neuroscience Biotechnology Infectious Diseases Virology Mathematical Sciences not elsewhere classified systemic lupus erythematosus several diagnostic criteria occurrence among females evaluating phenotype algorithms alzheimer &# 8217 diagnostics include estimates anticipated clinical profile specific pa align evaluating one pa sle closely matched phenotype evaluation across patient cohort returned omop data sources disease &# 8217 cohort diagnostics clinical characteristics xlink "> subjects identified source tool repeated diagnoses paper introduces offer insights notable differences misclassification errors level characterization level characteristics index date incidence rate driven approach consistently higher also observed
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