• IEEE Trans Biomed Eng · Feb 2017

    Review

    -Omic and Electronic Health Record Big Data Analytics for Precision Medicine.

    • Po-Yen Wu, Chih-Wen Cheng, Chanchala D Kaddi, Janani Venugopalan, Ryan Hoffman, and May D Wang.
    • IEEE Trans Biomed Eng. 2017 Feb 1; 64 (2): 263-273.

    ObjectiveRapid advances of high-throughput technologies and wide adoption of electronic health records (EHRs) have led to fast accumulation of -omic and EHR data. These voluminous complex data contain abundant information for precision medicine, and big data analytics can extract such knowledge to improve the quality of healthcare.MethodsIn this paper, we present -omic and EHR data characteristics, associated challenges, and data analytics including data preprocessing, mining, and modeling.ResultsTo demonstrate how big data analytics enables precision medicine, we provide two case studies, including identifying disease biomarkers from multi-omic data and incorporating -omic information into EHR.ConclusionBig data analytics is able to address -omic and EHR data challenges for paradigm shift toward precision medicine.SignificanceBig data analytics makes sense of -omic and EHR data to improve healthcare outcome. It has long lasting societal impact.

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