Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium

RESEARCH OBJECTIVE: To develop scalable informatics infrastructure for normalization of both structured and unstructured electronic health record (EHR) data into a unified, concept-based model for high-throughput phenotype extraction. MATERIALS AND METHODS: Software tools and applications were devel...

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Main Authors: Pathak, Jyotishman, Bailey, Kent R, Beebe, Calvin E, Bethard, Steven, Carrell, David S, Chen, Pei J, Dligach, Dmitriy, Endle, Cory M, Hart, Lacey A, Haug, Peter J, Huff, Stanley M, Kaggal, Vinod C, Li, Dingcheng, Liu, Hongfang, Marchant, Kyle, Masanz, James, Miller, Timothy, Oniki, Thomas A, Palmer, Martha, Peterson, Kevin J, Rea, Susan, Savova, Guergana K, Stancl, Craig R, Sohn, Sunghwan, Solbrig, Harold R, Suesse, Dale B, Tao, Cui, Taylor, David P, Westberg, Les, Wu, Stephen, Zhuo, Ning, Chute, Christopher G
Formato: Artigo
Idioma:Inglês
Publicado: BMJ Publishing Group 2013
Assuntos:
Research and Applications
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC3861933/
https://ncbi.nlm.nih.gov/pubmed/24190931
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1136/amiajnl-2013-001939
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