Koutkias V, Thiessard F
Yearb Med Inform. 2014 Aug 15;9(1):48-51. doi: 10.15265/IY-2014-0031.
To select best papers published in 2013 in the field of big data and smart health strategies, and summarize outstanding research efforts.
A systematic search was performed using two major bibliographic databases for relevant journal papers. The references obtained were reviewed in a two-stage process, starting with a blinded review performed by the two section editors, and followed by a peer review process operated by external reviewers recognized as experts in the field.
The complete review process selected four best papers, illustrating various aspects of the special theme, among them: (a) using large volumes of unstructured data and, specifically, clinical notes from Electronic Health Records (EHRs) for pharmacovigilance; (b) knowledge discovery via querying large volumes of complex (both structured and unstructured) biological data using big data technologies and relevant tools; (c) methodologies for applying cloud computing and big data technologies in the field of genomics, and (d) system architectures enabling high-performance access to and processing of large datasets extracted from EHRs.
The potential of big data in biomedicine has been pinpointed in various viewpoint papers and editorials. The review of current scientific literature illustrated a variety of interesting methods and applications in the field, but still the promises exceed the current outcomes. As we are getting closer towards a solid foundation with respect to common understanding of relevant concepts and technical aspects, and the use of standardized technologies and tools, we can anticipate to reach the potential that big data offer for personalized medicine and smart health strategies in the near future.
评选出2013年大数据与智能健康策略领域的最佳论文，并总结杰出的研究成果。
使用两个主要的文献数据库对相关期刊论文进行系统检索。所获参考文献分两个阶段进行评审，首先由两位栏目编辑进行盲审，然后由该领域公认的外部专家进行同行评审。
完整的评审过程选出了四篇最佳论文，展示了该专题的各个方面，其中包括：(a) 使用大量非结构化数据，特别是电子健康记录（EHR）中的临床记录进行药物警戒；(b) 通过使用大数据技术和相关工具查询大量复杂（结构化和非结构化）生物数据来发现知识；(c) 在基因组学领域应用云计算和大数据技术的方法，以及(d) 能够高性能访问和处理从EHR中提取的大型数据集的系统架构。
大数据在生物医学中的潜力已在各种观点文章和社论中得到明确。对当前科学文献的综述展示了该领域各种有趣的方法和应用，但目前的成果仍未达到预期。随着我们在相关概念和技术方面的共同理解以及标准化技术和工具的使用方面越来越接近坚实的基础，我们预计在不久的将来能够实现大数据为个性化医疗和智能健康策略带来的潜力。
