Inquiring Diagnosis System of Traditional Chinese Medicine

Although Chinese medicine treatments have become popular recently, the complicated Chinese medical knowledge has made it difficult to be applied in computer-aided diagnostics. The ability to model and use the knowledge becomes an important issue. In this paper, we define the diagnosis in Traditional Chinese Medicine (TCM) as discovering the fuzzy relations between symptoms and syndromes. An Ontology-oriented Diagnosis System (ODS) is created to address the knowledge-based diagnosis based on a well-defined ontology of syndromes. The ontology transforms the implicit relationships among syndromes into a machine-interpretable model. The clinical data used for feature selection is collected from a national TCM research institute in China, which serves as a training source for syndrome differentiation. The ODS analyzes the clinical cases to obtain a statistical mapping relation between each syndrome and associated symptom set, before rechecking the completeness of related symptoms via ontology refinement. Our diagnostic system provides an online web interface to interact with users, so that users can perform self-diagnosis. We tested 12 common clinical cases on the diagnosis system, and it turned out that, given the agree metric, the system achieved better diagnostic accuracy compared to nonontology method—92% of the results fit perfectly with the experts’ expectations.

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The Study on the Agreement between Automatic Tongue Diagnosis System and Traditional Chinese Medicine Practitioners

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2012/505063 ◽

2012 ◽

Vol 2012 ◽

pp. 1-9 ◽

Cited By ~ 20

Author(s):

Lun-chien Lo ◽

Yung-Fu Chen ◽

Wen-Jiuan Chen ◽

Tsung-Lin Cheng ◽

John Y. Chiang

Keyword(s):

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Personal Knowledge ◽

High Agreement ◽

Diagnosis System ◽

Tongue Diagnosis ◽

Objective Information ◽

Kappa Value ◽

Clinical Stability

Tongue diagnosis is an important practice in traditional Chinese medicine (TCM) for diagnosing diseases before determining proper means of treatments. Traditionally, it depends solely on personal knowledge and experience of the practitioner, thereby being criticized as lacking of objectivity. Currently, no research regarding intra- and inter-agreements of automatic tongue diagnosis system (ATDS) and TCM doctors has been conducted. In this study, the ATDS is developed to extract a variety of tongue features and provide practitioners with objective information to assist diagnoses. To evaluate the ATDS clinical stability, 2 sets of tongue images taken 1 hour apart from 20 patients with possible variations in lighting and extruding tongue, are employed to investigate intra-agreement of the ATDS, intra-agreement of the TCM doctors, and the inter-agreement between the ATDS and TCM doctors. The ATDS is shown to be more consistent with significantly higher intra-agreement than the TCM doctors (kappa value:0.93±0.06versus0.64±0.13) withP<0.001(Student’st-test). Inter-agreements between the ATDS and TCM doctors, as well as among the TCM doctors are both moderate. The high agreement of the ATDS can provide objective and reliable tongue features to facilitate doctor in making effective observation and diagnosis of specific diseases.

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TRADITIONAL CHINESE MEDICAL DIAGNOSIS SYSTEM OF ARRHYTHMIA

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237207000252 ◽

2007 ◽

Vol 19 (03) ◽

pp. 199-205

Author(s):

Lun Ci Yuan ◽

Chu Feng

Keyword(s):

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Medical Diagnosis ◽

Approximate Reasoning ◽

Diagnosis System ◽

Multiple Factors ◽

Medical Diagnosis System ◽

Traditional Chinese Medical

With the intention of creating excellence in Dr. Lun Ci Yuan's diagnosis system in traditional Chinese medicine, multiple factors, criteria and types technique based on approximate reasoning is developed in this paper. The technique can sum up an expert's experience into computer. The diagnosis system has been successfully used to diagnose and treat arrhythmia.

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