Toward automating an inference model on unstructured terminologies: OXMIS case study.
Most modern biomedical vocabularies employ some hierarchical representation that provides a "broader/narrower" meaning relationship among the "codes" or "concepts" found within them. Often, however, we may find within the clinical setting the creation and curation of unstructured custom vocabularies used in the everyday practice of classifying and categorizing clinical data and findings.A significant and widely used example of this lies in the General Practice Research Database which makes use of the Oxford Medical Information Systems (OXMIS) coding scheme to represent drugs and medical conditions. This scheme is intrinsically unstructured, is generally regarded as disorganized, and is not amenable to comparison with other hierarchically structured medical coding schemes. To improve processes of data analysis and extraction, we define a semantically meaningful representation of the OXMIS codes by way of the Unified Medical Language System (UMLS) Metathesaurus. A structure-imposing ontology mapping is created, and this process provides a complete illustration of a general semantic mapping technique applicable to unstructured biomedical terminologies.
Painter
Jeffery L
JL
GlaxoSmithKline, Research Triangle Park, NC 27709, USA. jeffery.l.painter@gsk.com
D001331:Automation; D059019:Clinical Coding; D019295:Computational Biology; D003198:Computer Simulation; D016208:Databases, Factual; D058006:General Practice; D006801:Humans; D016247:Information Storage and Retrieval; D007256:Information Systems; D012660:Semantics; D017432:Unified Medical Language System; D018875:Vocabulary, Controlled