Promises and Challenges of Big Data Computing in Health Sciences

Abstract

With the development of smart devices and cloud computing, more and more public health data can be collected from various sources and can be analyzed in an unprecedented way. The huge social and academic impact of such developments caused a worldwide buzz for big data. In this review article, we summarized the latest applications of Big Data in health sciences, including the recommendation systems in healthcare, internet-based epidemic surveillance, sensor-based health conditions and food safety monitoring, Genome-Wide Association Studies (GWAS) and expression Quantitative Trait Loci (eQTL), inferring air quality using big data and metabolomics and ionomics for nutritionists. We also reviewed the latest technologies of big data collection, storage, transferring, and the state-of-the-art analytical methods, such as Hadoop distributed file system, MapReduce, recommendation system, deep learning and network Analysis. At last, we discussed the future perspectives of health sciences in the era of Big Data.

DOI: 10.1016/j.bdr.2015.02.002

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@article{Huang2015PromisesAC, title={Promises and Challenges of Big Data Computing in Health Sciences}, author={Tao Huang and Liang Lan and Xuexian Fang and Peng An and Junxia Min and Fudi Wang}, journal={Big Data Research}, year={2015}, volume={2}, pages={2-11} }