Title :
CardioOWL: An ontology-driven expert system for diagnosing coronary artery diseases
Author :
Al-Hamadani, Baydaa
Abstract :
According to World Health Organization, coronary artery diseases are responsible for 17% of the death in the world. Diagnosing the disease in the right time could lower the danger that it may cause. This paper presents an expert system (CardioOWL) that has the ability to diagnose any kind of coronary artery diseases. CardioOWL supplies the expert with the diagnosing strategies that could be used and suggests the drugs and/or other required operations to be taken. CardioOWL depends on ontology knowledge about the patient´s symptoms to build the knowledge base and then it utilizes Semantic Web Rule Language (SWRL) to deduce the suitable medicine and the required operation for the patient. The system was tested by some general practitioners using several test cases. The system proves to have very good precession and recall.
Keywords :
diseases; expert systems; medical computing; ontologies (artificial intelligence); patient diagnosis; semantic Web; CardioOWL; SWRL; World Health Organization; coronary artery disease diagnosis; ontology knowledge; ontology-driven expert system; semantic Web rule language; Arteries; Conferences; Diseases; Expert systems; OWL; Ontologies; Open systems; Coronary Artery; Expert Systems; OWL; Ontology; SWRL;
Conference_Titel :
Open Systems (ICOS), 2014 IEEE Conference on
Conference_Location :
Subang
Print_ISBN :
978-1-4799-6366-9
DOI :
10.1109/ICOS.2014.7042642