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PubMed · 15360849

Mapping various information sources to a semantic network.

Abstract

Giessen Data Dictionary Server (GDDS) provides context sensitive information services to disparate clinical applications by automatically navigating a semantic network that stores medical knowledge. Mapping multiple information sources to single clinical application becomes a challenge due to different organization of semi-structured information sources. Linking huge unstructured information sources such as medical literature is even more challenging because we need to develop a mechanism to organize unstructured information and take into account the scalability issue. In this paper, we have successfully mapped two drug information sources by developing an independent subnet for each source and linking them at proper nodes. For medical literature, we have demonstrated that the semantic network of the Unified Medical Language Systems and human assigned topics to each document can be used to organize the large amount of medical literature into the framework of the GDDS service.

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BibTeXRIS

Wen Ruan, Thomas Buerkle, Joachim W Dudeck. 2004. Mapping various information sources to a semantic network.. https://pubmed.ncbi.nlm.nih.gov/15360849/

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Toward semantic interoperability in home health care: formally representing OASIS items for integration into a concept-oriented terminology.

OBJECTIVE: The authors aimed to (1) formally represent OASIS-B1 concepts using the Logical Observation Identifiers, Names, and Codes (LOINC) semantic structure; (2) demonstrate integration of OASIS-B1 concepts into a concept-oriented terminology, the Medical Entities Dictionary (MED); (3) examine potential hierarchical structures within LOINC among OASIS-B1 and other nursing terms; and (4) illustrate a Web-based implementation for OASIS-B1 data entry using Dialogix, a software tool with a set of functions that supports complex data entry. DESIGN AND MEASUREMENTS: Two hundred nine OASIS-B1 items were dissected into the six elements of the LOINC semantic structure and then integrated into the MED hierarchy. Each OASIS-B1 term was matched to LOINC-coded nursing terms, Home Health Care Classification, the Omaha System, and the Sign and Symptom Check-List for Persons with HIV, and the extent of the match was judged based on a scale of 0 (no match) to 4 (exact match). OASIS-B1 terms were implemented as a Web-based survey using Dialogix. RESULTS: Of 209 terms, 204 were successfully dissected into the elements of the LOINC semantics structure and integrated into the MED with minor revisions of MED semantics. One hundred fifty-one OASIS-B1 terms were mapped to one or more of the LOINC-coded nursing terms. CONCLUSION: The LOINC semantic structure offers a standard way to add home health care data to a comprehensive patient record to facilitate data sharing for monitoring outcomes across sites and to further terminology management, decision support, and accurate information retrieval for evidence-based practice. The cross-mapping results support the possibility of a hierarchical structure of the OASIS-B1 concepts within nursing terminologies in the LOINC database.

Dictionaries, Medical as Topic↗