Toward a Literature-Driven Definition of Big Data in Healthcare.

Toward a Literature-Driven Definition of Big Data in Healthcare.
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DOI:
10.1155/2015/639021
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发表时间:
2015
影响因子:
--
通讯作者:
Chazard E
Chazard E
中科院分区:
生物学3区
文献类型:
--
作者:
Baro E;Degoul S;Beuscart R;Chazard E

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目标。本研究的目的是为医疗保健中的大数据提供一个定义。方法。对2014年5月9日之前发表的PubMed文献进行了系统检索。我们注意到描述数据集的所有论文的统计个体数(n)和变量数(p)。这些论文按研究领域分类。作者赋予大数据的特征也被考虑在内。在此基础上,提出了大数据的定义。结果。共收录论文196篇。大数据可以定义为Log (n∗p)≥7的数据集。大数据的特点是种类多、速度快。大数据对准确性、工作流程的各个方面、提取有意义的信息以及信息共享提出了挑战。大数据需要新的计算方法来优化数据管理。相关概念包括数据重用、错误知识发现和隐私问题。结论。大数据是由容量定义的。不应将大数据与数据重用混淆:数据可以很大,但不会被重用用于其他目的,例如在组学中。相反,数据可以重复使用,而不必很大,例如,电子医疗记录(EMR)数据的二次使用。
Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.
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