MEDICAL ONTOLOGY ENGINEERING FOR HEART DISEASES: A PATHOLOGICAL APPROACH

Abstract

Heart disease continues to be one of the leading causes of death worldwide, making it essential to develop accurate tools that combine both clinical insight and pathological evidence. In this paper, we developed an Ontology-based framework aimed at improving the understanding and classification of heart diseases from a pathology-centered perspective. The methodology followed well-established Ontology engineering practices such as "Methodology" and the NeOn framework. We began by gathering expert knowledge from cardiologists and pathologists, supported by trusted clinical guidelines and textbooks. The heart disease Ontology was built using the OWL language in Protégé, and it captures meaningful links between symptoms, clinical signs, lab tests, and treatment options. A team of medical specialists reviewed the Ontology through iterative validation steps to ensure its clinical accuracy and usefulness. When applied to real patient records, the system showed a noticeable improvement in diagnostic consistency and precision. These results highlight the practical value of medical ontologies in supporting physician decision-making and improving integration across digital health systems, especially when paired with AI-powered diagnostic tools.