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
פורמט: Artigo
שפה:Inglês
יצא לאור: BMJ Publishing Group 2013
נושאים:
Research and Applications
גישה מקוונת: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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