title: Operationalizing Semantic Medline for meeting the information needs at point of care.
abstract: 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.
authors: Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN.
authors: Majid
authors: M
authors: Rastegar-Mojarad
authors: Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN.
authors: Dingcheng
authors: D
authors: Li
authors: Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN.
authors: Hongfang
authors: H
authors: Liu