Towards an ontology-based decision support system for syndrome-differentiation and treatment of Psoriasis Vulgaris in Traditional Chinese Medicine

Abstract Background: Psoriasis is a chronic, non-communicable, painful, disfiguring and disabling disease, which is not curable and strongly declines the patients’ quality of life (QoL). However, diagnose and treatment in traditional Chinese medicine (TCM) based on syndrome differentiation has been used in practice for a long time and has also achieved some effect. Though, up to now, only few studies are available reporting on the use of semantic technologies and pertain to knowledge systems that use TCM-syndrome differentiation for information retrieval and automated reasoning. Nowadays, the diagnosis in TCM relies mainly on the personal expertise and clinical experience of the doctors. For various reasons, misdiagnoses or missed diagnoses cannot be completely excluded, leading to unexpected results.Methods In the present paper, we developed a domain ontology for syndrome differentiation of psoriasis vulgaris (PV). For this purpose, we used the ontology editor Protégé and applied a top-down approach which adopts the framework of general formal ontology (GFO) and its middle-level core ontology GFO-TCM. Furthermore, we implemented a prototype which is based on this ontology. Additionally, we also used a case-database for CBR (Case Based Reasoning) combined with fuzzy pattern recognition.Results: A prototype for diagnosis and treatment of psoriasis vulgaris, named ONTOPV-system, is proposed which is based on the principle of syndrome differentiation and treatment in TCM; this system realizes an expert-assisted decision support method which relies on a domain ontology, uses fuzzy logic reasoning, and case retrieval and is intended to support clinical diagnostic decisions for TCM practitioners.Conclusions: We designed and implemented a prototype for psoriasis diagnosis in terms of syndrome differentiation. The system realizes the basic functionalities of data collection, querying, browsing and navigation, and supports rule-based knowledge reasoning and integrates approximative reasoning, based on CBR and fuzzy logic. The system provides users with clinical decision support for TCM syndrome differentiation in diagnosis of psoriasis. In addition, it comprises a domain knowledge base of psoriasis, which is developed in the GFO framework with good extensibility.