健康和疾病中的大数据:为发现和验证而重新处理信息

R. Yeung, E. Capobianco
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引用次数: 0

摘要

关于大数据在健康和疾病领域的新兴作用,人们已经说了很多。为了应对个性化和精准医疗的出现,以及与“组学革命”和电子健康记录中心相关的大规模数据工作正在越来越多地进行。大数据已经证明,其复杂的特性给医学和公共卫生的许多部门广泛识别、分析和审查的研究问题带来了优势因素和瓶颈。由于大数据最显著的特征是“多样性”,这意味着异质性,当协调和互操作性策略发挥主要作用时,我们在复杂疾病背景下的知识可能会从不同数据类型的融合中受益匪浅。我们讨论一个例子,糖尿病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big data in health and disease: re-processing information for discovery and validation
A lot has been already said about the emerging role of big data in health and disease. Large scale data efforts are increasingly being undertaken in response to the advent of Personalized and Precision Medicine and in association with both the “omics revolution” and the Electronic Health Records centrality. big data have demonstrated that their complex characteristics bring both strength factors and bottlenecks to research problems widely identified, analyzed and reviewed across many sectors of medicine and public health. As the most significant feature of big data is “variety”, and this implies heterogeneity, our knowledge in complex disease contexts may substantially benefit from the fusion of different data types when a major role is assigned to harmonization and interoperability strategies. We discuss of an example, diabetes.
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CiteScore
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