Abstract
Medical Guidelines pay an important role in medical decision making systems. Medical guidelines are usually involved with event-related actions or procedure. However, little research has been done on how event-related medical guidelines can be converted into its semantic representation such as RDF/OWL data. This paper proposes an approach of automatic generation of semantic data for event-related medical guidelines. This generation is achieved by using the logic programming language Prolog with the support of medical ontologies such as SNOMED CT. We will report the experiments with the automatic generation of the semantic data for event-related Chinese medical guidelines, and show the relevant results.
The National Natural Science Foundation of China under Grant Nos. 60803160, 61100133, 61272110; The major program of the National Social Science Foundation under Grant No. 11&ZD189; Provincial Key Laboratory Open Fund (znss2013B011); Hubei Provincial Education Department under Grant (Q20151111); Wuhan University of Science and Technology under grants (2013xz012,2014xz019); Rui Qiao is the corresponding author of this paper.
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Fan, Y., Qiao, R., Gu, J., Huang, Z. (2016). Automatic Generation of Semantic Data for Event-Related Medical Guidelines. In: Qi, G., Kozaki, K., Pan, J., Yu, S. (eds) Semantic Technology. JIST 2015. Lecture Notes in Computer Science(), vol 9544. Springer, Cham. https://doi.org/10.1007/978-3-319-31676-5_11
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DOI: https://doi.org/10.1007/978-3-319-31676-5_11
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