Rastegar-Mojarad Majid, Li Dingcheng, Liu Hongfang
Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN.
AMIA Jt Summits Transl Sci Proc. 2015 Mar 25;2015:152-6. eCollection 2015.
Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible.
科学文献是在医疗点提供决策支持的常用资源之一。非常希望引入最相关的文献来支持基于证据的临床决策过程。受语义增强信息检索最新进展的推动,我们开发了一个系统,旨在引入语义丰富的文献“语义医学文献数据库(Semantic Medline)”,以满足医疗点的信息需求。本研究报告了我们为使该系统能够实时运行所做的工作。我们证明,将关系数据库实现迁移到非关系型数据库(NoSQL,即“不仅仅是SQL”)实现可显著提高性能,并使在医疗点决策支持中使用语义医学文献数据库成为可能。