A FRAMEWORK FOR ONTOLOGY- BASED DIABETES DIAGNOSIS USING BAYELSIAN OPTIMIZATION TECHNIQUE

Diabetes Management System (DMS) is a computer-based system which aid physicians in properly diagnosing diabetes mellitus disease in patients. The DMS is essential in making individuals who have diabetes aware of their state and type. Existing approaches employed have not been efficient in considering all the diabetes type as well as making full prescription to diabetes patients. In this paper, a framework for an improved Ontology-based Diabetes Management System with a Bayesian optimization technique is presented. This helped in managing the diagnosis of diabetes and the prescription of treatment and drug to patients using the ontology knowledge management. The framework was implemented using Java programming language on Netbeans IDE, Protégé 4.2 and mysql. An extract of the ontology graph and acyclic probability graph was shown. The result showed that the nature of Bayesian network which has to do with statistical calculations based on equations, functions and sample frequencies led to more precise and reliable outcome.   &nbsp

A Systematic Review of Health Care Ontology

Objective: The study sought to extracts information about the steps, methods, techniques, initiatives and strategies that is use in establishing ontology in the medical sector. Methods: The guideline that was employed for conducting the systematic review in this research work is that which was proposed by Kitchenham. The Google Scholar, Scopus and Web of science were searched for proceedings from conferences and journal papers between 2009 and 2018. Articles focusing on health care and ontology, health ontology and diagnosis system were selected. The AND operator was used in the Boolean language construction for the article search to limit articles presented to those that actually apply Ontology in the Health care. Selected articles were considered eligible based on their studies appropriately fitting into providing answers for the research questions that were presented in this research work within the last 10 years. Results: Twenty (20) research articles were included in the review; of the initiatives of the research works considered, Seven (7) were of Methodology, Two (2) were Technique based, Three (3) were Framework based, Two (2) were Process based while Six (6) were extensions of those in existence. Conclusions: The approaches considered were ontology based in terms of the use of Protégé-owl editor tool, SPARQL, Protégé 4, OWL 2, OWL, RDF, SNOMED CT. The main contributions include but not limited to Modelling of knowledge representation using Protégé for relating data and concepts with references to diabetes diseases, mobile based health care ontology, classification of diseases based on phenotypes, improvement in service delivery and availability of reliable health data. This Ontology heath care review which was carried out shows the need for Ontology based models to improve health service delivery for both the users (patients) and the care providers