Abstract
This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various – omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given.
Highlights
IntroductionTo obtain the best services and care for the patients, healthcare organizations in many countries have proposed various models of healthcare information systems
To obtain the best services and care for the patients, healthcare organizations in many countries have proposed various models of healthcare information systems. These models for personalized, predictive, participatory and preventive medicine are based on using of electronic health records (EHRs) and huge amounts of complex biomedical data and high-quality – omics data [1]
The processing of these big data in medicine and healthcare can be accelerating by using cloud computing and powerful multicore central processing units (CPUs), graphics processing units (GPU) and field-programmable gate arrays (FPGAs) with parallel processing methods
Summary
To obtain the best services and care for the patients, healthcare organizations in many countries have proposed various models of healthcare information systems These models for personalized, predictive, participatory and preventive medicine are based on using of electronic health records (EHRs) and huge amounts of complex biomedical data and high-quality – omics data [1]. Genomics and postgenomics technologies produce huge amounts of raw data about complex biochemical and regulatory processes in the living organisms [2]. These -omics data are heterogeneous, and very often they are stored in different data formats. Last section concludes this paper with discussion and further works
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