A medical decision support system for cardiovacsular disease based on ontology learning

This paper presents our decision support system “CardioSAD” that aims to assist cardiologists to make relevant decisions for patients who are at risk cardiovascular disease. The main idea is to analyse clinical practice guidelines (there are a documents that contain a set of recommendations and medical knowledge) to enrich and exploit an existing ontology. The process of enrichment is driven by the task of ontology learning. We start by pre-processing the text and extracting the relevant concepts. Then, the OWL DL axioms and SWRL rules will be used to enrich our ontology. These rules will be inferred for suggesting appropriate recommendations to the doctors.