An Ontology Driven Hormone Imbalance Diagnostic System

Hormone imbalances are known tohaveclosely related symptoms. Thyroid hormone imbalance, for example, shares 75% of its symptoms with Testosterone and cortisol hormone imbalancesmaking it difficult to accurately diagnose the hormone imbalance. A review of anontology based system that diagnoses hormone imbalanceonly diagnoses thyroid hormone imbalance without taking into account of the similarities of symptoms with testosterone and cortisol imbalance. This can lead to an error in diagnosis. This workpresents an ontology based diagnosissystem that diagnoses thyroid hormone imbalance taking into account similar hormone imbalances (cortisol and testosterone) thereby improving the number of correct diagnosis the system makes. The systemmakes use of a knowledge base built using Web Ontology Language (OWL), a carefully designed interface that allows users to interact with the knowledge base implemented with JavaFX. Jena reasoning engine and SPARQL were used to provide both reasoning and querying services respectively.The findings of this study reveal an improved ontology model as a result of adding related hormone imbalances.A simulation program was developed to measure the number of correct diagnosis the developed system makes, and the results revealed the system made7 times more correct diagnosis than the existing system.

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