Abstract
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.
Highlights
Applying mathematical models and information technologies to medical intelligence has long been a hot spot in the academic research domains and real-life health care applications
We propose a simple but useful diagnostic system based on a domain ontology proposed by professional Traditional Chinese Medicine (TCM) experts, which is supposed to formalize the hidden knowledge and be imported into the diagnostic process
Based on the methods we proposed, we implemented an interactive medical diagnostic platform deployed on web browser
Summary
Applying mathematical models and information technologies to medical intelligence has long been a hot spot in the academic research domains and real-life health care applications. The Ontology-oriented Diagnostic System (ODS) address these problems by applying ontology representation as one of the techniques of semantic technologies, to systematize the important but usually hidden knowledge of syndrome relationships. It captures all the subtle relationships among syndromes as a terminology base and stores it in an ontology file.
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