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IEEE Trans Biomed Eng. 2017 Feb;64(2):263-273. doi: 10.1109/TBME.2016.2573285. Epub 2016 Oct 10.

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

Abstract

OBJECTIVE:

Rapid 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.

METHODS:

In this paper, we present -omic and EHR data characteristics, associated challenges, and data analytics including data preprocessing, mining, and modeling.

RESULTS:

To 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.

CONCLUSION:

Big data analytics is able to address -omic and EHR data challenges for paradigm shift toward precision medicine.

SIGNIFICANCE:

Big data analytics makes sense of -omic and EHR data to improve healthcare outcome. It has long lasting societal impact.

PMID:
27740470
PMCID:
PMC5859562
DOI:
10.1109/TBME.2016.2573285
[Indexed for MEDLINE]
Free PMC Article

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