A Prototype for Diagnosis of Psoriasis in Traditional Chinese Medicine

Abstract

Psoriasis is a chronic, non-communicable, painful, disfiguring and disabling disease for which there is no cure, with great negative impact on patients' quality of life (QoL). Diagnosis and treatment with traditional Chinese medical technique based on syndrome differentiation has been used in practice for a long time and proven effective, though, up to now, there are only a few available studies about the use of semantic technologies and the knowledge systems that use Traditional Chinese Medicine (TCM)-syndrome differentiation for information retrieval and automated reasoning. In this paper we use semantic techniques based on ontologies to develop a prototypical system for the diagnosis of Psoriasis. For this purpose, a domain ontology is developed for syndrome differentiation of psoriasis vulgaris (PV). This ontology is founded on an adapted version of the general formal ontology (GFO), with the evidence-based clinical practice guideline of TCM for psoriasis vulgaris (Guideline 2013) as the primary data sources. The implemented prototype, called ONTOPV, contains this domain ontology and is aimed at a decision support system for diagnosis and treatment of PV. This system uses a case-database for Case Based Reasoning (CBR), combined with fuzzy pattern recognition. Experimental results show that the ONTOPV realizes the basic functionalities of data collection, querying, browsing and navigation, and supports rule-based knowledge reasoning, and integrates fuzzy pattern recognition. It can provide users with clinical decision support for TCM syndrome differentiation in diagnosis of psoriasis.