A study of Knowledge Modeling using abstract concepts in Traditional East Asian Medicine.
- Author:
Seon Ho KIM
1
;
Hyun Kyung KIM
;
Ki Wang KIM
;
Kyung Mo PARK
Author Information
1. Department of Biomedical Engineering, Kyung Hee University, Korea. saenim@khu.ac.kr
- Publication Type:Original Article
- Keywords:
Knowledge Representation;
Traditional Medicine;
Diagnosis;
Expert System
- MeSH:
Aluminum Hydroxide;
Carbonates;
Expert Systems;
Humans;
Lifting;
Logic;
Medicine, East Asian Traditional;
Medicine, Traditional;
Yin-Yang
- From:Journal of Korean Society of Medical Informatics
2008;14(4):387-394
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
OBJECTIVE: This research is focused on modeling the diagnostic knowledge in traditional medicine. Unlike the previous studies which have dealt mainly with the standardized heuristic knowledge for diagnosis, we investigated the logical procedures and a set of source knowledge which the standardized diagnosis has been based on. These procedures and knowledge are related to Yin-Yang principle and their medical derivatives which are believed to interact with the heuristic knowledge for diagnosis through analogical reasoning. METHOD: we analyzed disorders which have been specified in traditional medicine and their signs and symptoms on the diagnostic criteria defined by Korean Institute of Oriental Medicine. Based on the conventional knowledge, all the symptoms were analyzed into elementary abstractive concepts so that we represented their properties by the principles mentioned above. And then we analyzed the procedures to link the disorders to their assigned sign and symptoms. RESULTS: Based on the proposed methodology, the diagnostic knowledge in traditional medicine was represented as rules in our ontology which was written by OpenCyc system. By applying these rules to the properties of the symptoms that have been derived from a patient, the patient's disorder can be determined. And this preliminary algorithm was implemented to be able to obtain a limited diagnostic result for individual patients. CONCLUSION: This research developed an analytic and consequently flexible diagnostic knowledge system for traditional medicine than the previous studies. These results will be extended to developing an analogical reasoning algorithm by the authors. It is also necessary, however, to improve them both by providing more practical diagnostic knowledge in such medicine and by carrying out clinical evaluations.
