domingo, 23 de octubre de 2016

Advanced Big Data Analytics for -Omic Data and Electronic Health Records: Toward Precision Medicine. - PubMed - NCBI

Advanced Big Data Analytics for -Omic Data and Electronic Health Records: Toward Precision Medicine. - PubMed - NCBI



 2016 Oct 10. [Epub ahead of print]

Advanced Big Data Analytics for -Omic Data and Electronic Health Records: Toward 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 health care.

METHODS:

In this article, we present -omic and EHR data characteristics, associated challenges, and data analytics including data pre-processing, 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 towards 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
 
DOI:
 
10.1109/TBME.2016.2573285

[PubMed - as supplied by publisher]