Open AccessA FRAMEWORK FOR ONTOLOGY- BASED DIABETES DIAGNOSIS USING BAYELSIAN OPTIMIZATION TECHNIQUE
Author(s) -
F. M. OKIKIOLA,
O. S. ADEWALE,
Abiodun Muyideen Mustapha,
A. M. IKOTUN,
O. L. LAWAL
Publication year - 2019
Publication title -
journal of natural sciences, engineering and technology/journal of natural science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2315-7461
pISSN - 2277-0593
DOI - 10.51406/jnset.v17i1.1906
Subject(s) - ontology , computer science , diabetes mellitus , java , graph , bayesian network , medical prescription , diabetes management , machine learning , medicine , type 2 diabetes , theoretical computer science , programming language , nursing , philosophy , epistemology , endocrinology
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.