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
Formáid: Artigo
Teanga:Inglês
Foilsithe: BMJ Publishing Group 2013
Ábhair:
Research and Applications
Rochtain Ar Líne: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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