Introduction: Decision making Support Systems, along with Semantic Web technology, develop a new approach to help physicians in the diagnosis of a variety of illnesses. On the other hand, medical ontology is a knowledge model of clinical domain including all the concepts related to the diagnosis, treatment, clinical procedures and patient data.
Methods: In this developmental-applied study, a system for the diagnosis of diseases in various fields of medicine based on the chest pain as a common symptom has been developed. Various symptoms, diagnostic tests and also the intervening nature of disease, meaning that one disease could be a diagnostic symptom of another disease, have been considered in this system and by applying it, real data of patients hospitalized in Shafa hospital in Kerman/ Iran have been studied through Protege software and program language based on Jena rule.
Results: The proposed method was compared to conventional and multilevel methods in regard to the disease diagnosis and the number of required rules. The proposed method, as opposed to the conventional method, is capable of detecting disease at the most inner level. Furthermore the proposed multi-level and entity-related method is capable of detecting disease by means of just seven rules even in the worst cases.
Conclusion: Multilevel entity-based approach accompanied with semantic technology is an effective approach in medical diagnosis systems.