about
Review and evaluation of electronic health records-driven phenotype algorithm authoring tools for clinical and translational research.Developing a data element repository to support EHR-driven phenotype algorithm authoring and execution.Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals.A Prototype for Executable and Portable Electronic Clinical Quality Measures Using the KNIME Analytics Platform.Desiderata for computable representations of electronic health records-driven phenotype algorithms.A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and ExecutionCombining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performanceTranscription factor ETV1 is essential for rapid conduction in the heart.Neuronal activity modifies the DNA methylation landscape in the adult brainPhenome-Wide Association Study of Rheumatoid Arthritis Subgroups Identifies Association Between Seronegative Disease and Fibromyalgia.Effects of G6pc2 deletion on body weight and cholesterol in mice.Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record.ReplyA case study evaluating the portability of an executable computable phenotype algorithm across multiple institutions and electronic health record environments
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description
researcher ORCID ID = 0000-0001-6029-458X
@en
wetenschapper
@nl
name
Huan Mo
@ast
Huan Mo
@en
Huan Mo
@nl
type
label
Huan Mo
@ast
Huan Mo
@en
Huan Mo
@nl
prefLabel
Huan Mo
@ast
Huan Mo
@en
Huan Mo
@nl
P106
P31
P496
0000-0001-6029-458X