id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_ozfgaeogofdlroxd65simz73ay	Estefanía Caballero-Ruiz	Automatic classification of glycaemia measurements to enhance data interpretation in an expert system for gestational diabetes	2016	11	.pdf	application/pdf	9925	1171	66	Automatic classification of glycaemia measurements to enhance data interpretation in an expert system for gestational diabetes Expert systems for diabetes care need to automatically evaluate glycaemia measurements in relationship Different machine learning techniques were studied in order to design the best classification algorithm in terms of accuracy. The classification module was integrated in the Sinedie expert system for gestational diabetes care and was evaluated in a clinical environment for 8 months with 42 patients. The majority of studies available in literature about expert systems do not explicit describe the method used to retrieve the associated meal and moment of measurement of glycaemia data or classifier to associate the appropriate meal and moment of measurement to each glycaemia data downloaded from a glucose Table 1 shows the results of the statistical study about measurement time variability of each patient over the four meal intervals 	./cache/work_ozfgaeogofdlroxd65simz73ay.pdf	./txt/work_ozfgaeogofdlroxd65simz73ay.txt