Big Data Science and Its Applications in Health and Medical Research: Challenges and Opportunities
- *Corresponding Author:
- Liang Y
Department of Family and Community Health
University of Maryland, Baltimore
MD 21201, USA
E-mail: [email protected]
Received Date: April 07, 2016; Accepted Date: May 07, 2016; Published Date: May 14, 2016
Citation: Liang Y, Kelemen A (2016) Big Data Science and Its Applications in Health and Medical Research: Challenges and Opportunities. J Biom Biostat 7:307. doi:10.4172/2155-6180.1000307
Copyright: © 2016 Liang Y, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Recently, Big Data science has been a hot topic in the scientific, industrial and the business worlds. The healthcare and biomedical sciences have rapidly become data-intensive as investigators are generating and using large, complex, high dimensional, and diverse domain specific datasets. This paper provides a general survey of recent progress and advances in Big Data science, healthcare, and biomedical research. Big Data science impacts, important features, infrastructures, and basic and advanced analytical tools are presented in detail. Additionally, various challenges, debates, and opportunities inside this quickly emerging scientific field are explored. The human genome research, one of the most promising medical and health areas as an example and application of Big Data science, is discussed to demonstrate how the adaptive advanced computational analytical tools could be utilized for transforming millions of data points into predictions and diagnostics for precision medicine and personalized healthcare with better patient outcomes.