Knowledge-driven diagnostic system for traditional Chinese medicine

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Abstract

Recognizing diseases from theoretical perspective can help ordinary people have a general understanding of medicine. The usual process of identifying syndromes or diseases in Traditional Chinese Medicine (TCM) is by confirming the frequently symptom patterns. Semantic Web and ontologies introduce well-structured controlled vocabularies for biomedical science. The direct correspondence between symptoms and syndromes can be formatted to semantic inference rules as a additional knowledge upon a medical ontology. In this paper, we present a simplified rule-based diagnostic system for febrile disease theory in TCM, which make use of the capability of semantic inference based on medical ontology. Actually the method is rather general for logic-based medical diagnosis, and we show that without interpreting clinical data, the medical knowledge itself can be applied to do basic clinical diagnosis. © 2012 Springer-Verlag.

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Gu, P., & Chen, H. (2012). Knowledge-driven diagnostic system for traditional Chinese medicine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7185 LNCS, pp. 258–267). https://doi.org/10.1007/978-3-642-29923-0_17

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