@article{belle_big_2015,
	title = {Big {Data} {Analytics} in {Healthcare}.},
	volume = {2015},
	issn = {2314-6141 2314-6133},
	doi = {10.1155/2015/370194},
	abstract = {The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to  accumulate, manage, analyze, and assimilate large volumes of disparate, structured,  and unstructured data produced by current healthcare systems. Big data analytics has  been recently applied towards aiding the process of care delivery and disease  exploration. However, the adoption rate and research development in this space is  still hindered by some fundamental problems inherent within the big data paradigm.  In this paper, we discuss some of these major challenges with a focus on three  upcoming and promising areas of medical research: image, signal, and genomics based  analytics. Recent research which targets utilization of large volumes of medical  data while combining multimodal data from disparate sources is discussed. Potential  areas of research within this field which have the ability to provide meaningful  impact on healthcare delivery are also examined.},
	language = {eng},
	journal = {BioMed research international},
	author = {Belle, Ashwin and Thiagarajan, Raghuram and Soroushmehr, S. M. Reza and Navidi, Fatemeh and Beard, Daniel A. and Najarian, Kayvan},
	year = {2015},
	pmid = {26229957},
	pmcid = {PMC4503556},
	keywords = {*Statistics as Topic, Datasets as Topic, Delivery of Health Care/*methods, Genomics, Humans, Image Processing, Computer-Assisted, Signal Processing, Computer-Assisted},
	pages = {370194},
}

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In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. 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It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. 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