Diagnosing Heart Diseases Using Ontology and SWRL Rules

Abstract

Heart disease is the most common disease worldwide which is considered the main cause of death. According to cardiologists in Palestine, the heart disease was the main cause of death among the Palestinians, at a rate of 27.5% of all deaths. The differential diagnosis between different types of heart diseases requires the results of several clinical tests. The patient's symptoms alone are not sufficient to give an accurate diagnosis because many types of heart diseases have the same symptoms. Currently there is no specific system in the domain of heart diseases in Palestine. Also, available medical systems do not employ semantic approaches, they are just using database-oriented methodologies. They are not flexible and adaptable to complex requirements and processes and lack intelligence. This work aims to improve the diagnosis of heart diseases by exploiting Semantic Web technologies. We use ontology and Semantic Web Rule Language (SWRL) to diagnose heart diseases. We have built a domain ontology (HeartOnt) that covers domain knowledge of heart diseases. The ontology contains terms, relationship and properties to be used in the approach of diagnosing heart diseases. SWRL rules are created from valid relationships between ontology concepts to detect heart disease and estimate the risk of heart disease. The rules are used to infer new knowledge from the ontology, knowledge base and patient data. The proposed system was tested using a sample set of patients with heart diseases provided by a domain expert. Results have shown that the system have correctly diagnosed 27 out of the 30 patients (ratio of correctness is 90%). Keywords: Diagnosis heart diseases, Semantic Web, Ontology, SWRL Rules, OWL, Inference Engine.