id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_mdbxzh27xbgwveaawrkit36ry4	Ibrahim M. Ahmed	Reasoning Techniques for Diabetics Expert Systems	2015	8	.pdf	application/pdf	4691	378	56	addition, this paper proposes the best reasoning technique for diabetic expert systems. Keywords: Diabetes;Rule based reasoning;case based reasoning; fuzzy reasoning; ontological reasoning; medical expert systems; 2.4 Ontological Case Base reasoning Methodology for Diabetes Management Domain knowledge ontology supports the implementation of intelligent Case Based Reasoning (CBR) systems. N. Nnamoko et.al (2013) [14] proposed a fuzzy expert system framework that combines case-based and rulebased reasoning effectively to produce a usable tool for Type 2 Diabetes Mellitus (T2DM) management, to produce Tables 1, 2 , 3 and 4 show the results of our analysis of the expert systems in diabetes domain, based on the type of • The reasoning based of the system, it is either rule or case or fuzzy or ontology. Table 1: Rule based expert systems for diabetes Table 2: Case based reasoning expert systems for diabetes Table 4: Ontology case based reasoning expert systems for diabetes 	./cache/work_mdbxzh27xbgwveaawrkit36ry4.pdf	./txt/work_mdbxzh27xbgwveaawrkit36ry4.txt