Dhombres F, Charlet J
Yearb Med Inform. 2017 Aug;26(1):148-151. doi: 10.15265/IY-2017-030. Epub 2017 Sep 11.
To select, present, and summarize the best papers published in 2016 in the field of Knowledge Representation and Management (KRM). A comprehensive and standardized review of the medical informatics literature was performed based on a PubMed query. Among the 1,421 retrieved papers, the review process resulted in the selection of four best papers focused on the integration of heterogeneous data via the development and the alignment of terminological resources. In the first article, the authors provide a curated and standardized version of the publicly available US FDA Adverse Event Reporting System. Such a resource will improve the quality of the underlying data, and enable standardized analyses using common vocabularies. The second article describes a project developed in order to facilitate heterogeneous data integration in the i2b2 framework. The originality is to allow users integrate the data described in different terminologies and to build a new repository, with a unique model able to support the representation of the various data. The third paper is dedicated to model the association between multiple phenotypic traits described within the Human Phenotype Ontology (HPO) and the corresponding genotype in the specific context of rare diseases (rare variants). Finally, the fourth paper presents solutions to annotation-ontology mapping in genome-scale data. Of particular interest in this work is the Experimental Factor Ontology (EFO) and its generic association model, the Ontology of Biomedical AssociatioN (OBAN). Ontologies have started to show their efficiency to integrate medical data for various tasks in medical informatics: electronic health records data management, clinical research, and knowledge-based systems development.
筛选、展示和总结2016年发表在知识表示与管理(KRM)领域的最佳论文。基于PubMed查询对医学信息学文献进行了全面且标准化的综述。在检索到的1421篇论文中,综述过程筛选出了四篇最佳论文,这些论文聚焦于通过术语资源的开发和对齐来整合异构数据。在第一篇文章中,作者提供了公开可用的美国食品药品监督管理局不良事件报告系统的精选和标准化版本。这样的资源将提高基础数据的质量,并能够使用通用词汇进行标准化分析。第二篇文章描述了一个为促进i2b2框架中的异构数据集成而开展的项目。其独特之处在于允许用户整合用不同术语描述的数据,并构建一个新的知识库,该知识库具有一个能够支持各种数据表示的独特模型。第三篇论文致力于在罕见病(罕见变异)的特定背景下,对人类表型本体(HPO)中描述的多个表型特征与相应基因型之间的关联进行建模。最后,第四篇论文提出了基因组规模数据中注释 - 本体映射的解决方案。这项工作中特别值得关注的是实验因子本体(EFO)及其通用关联模型——生物医学关联本体(OBAN)。本体已开始展现出其在医学信息学的各种任务中整合医学数据的效率:电子健康记录数据管理、临床研究以及基于知识的系统开发。