A self-learning expert system for diagnosis in traditional Chinese medicine
Expert Systems with Applications: An International Journal
Ontology development for unified traditional Chinese medical language system
Artificial Intelligence in Medicine
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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.