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

Authors :: Wu PY
Cheng CW
Kaddi CD
Venugopalan J
Hoffman R
Wang MD
Source :: IEEE transactions on bio-medical engineering [IEEE Trans Biomed Eng] 2017 Feb; Vol. 64 (2), pp. 263-273. Date of Electronic Publication: 2016 Oct 10.
Publication Year :: 2017
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.<br />Methods: In this paper, we present -omic and EHR data characteristics, associated challenges, and data analytics including data preprocessing, mining, and modeling.<br />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.<br />Conclusion: Big data analytics is able to address -omic and EHR data challenges for paradigm shift toward precision medicine.<br />Significance: Big data analytics makes sense of -omic and EHR data to improve healthcare outcome. It has long lasting societal impact.