Big Data Analytics in Medicine and Healthcare.
Big Data Analytics in Medicine and Healthcare.
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DOI：
10.1515/jib-2017-0030
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发表时间：
2018-05-10
影响因子：
1.9
通讯作者：
Chen M
中科院分区：
文献类型：
--
作者：
Ristevski B;Chen M
本文对大数据进行了调查，重点介绍了医学和医疗保健领域的大数据分析。描述了大数据的特征：价值、量、速度、种类、准确性和可变性。医学和医疗保健领域的大数据分析涵盖了大量复杂异构数据的整合和分析，如各种组学数据（基因组学、表观基因组学、转录组学、蛋白质组学、代谢组学、相互作用组学、药物基因组学、疾病组学）、生物医学数据和电子健康记录数据。我们强调大数据隐私和安全方面的挑战性问题。针对大数据的特点，给出了使用合适且有发展前景的开源分布式数据处理软件平台的一些方向。
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.