Risk assessment prediction of hypertension and its associated diseases — An ontology driven model

This research paper presents an intelligent system to predict the risk assessment of hypertension in three main related areas like diabetes, cardiovascular problems, and kidney disorders. The system is targeted on patients in Sultanate of Oman. Currently there is no specific system in the domain of hypertension or its associated diseases in the Sultanate. Also currently available medical systems in Oman do not employ an intelligent approach; they are just using database-oriented methodologies. They are not flexible and adaptable to complex requirements and processes and lack intelligence. We propose a system with ontologies as knowledge base (medical knowledge base), patient medical profile to be stored in a semantic way and an inference mechanism to extract data in the decision making process. Ontology is among the most powerful tools to encode medical knowledge formally. Since the knowledge base is constructed through ontology, it can be easily reused and extended in a variety of different problems. The proposed system which is an interactive decision support system (DSS) is a partial replacement of traditional database oriented system which is not capable of finding out patient risk analysis in an intelligent way.