データマイニングによる血糖値の変動傾向の推定

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Many diabetic patients carry a portable self-measuring blood glucose monitor, withdraw their own blood and examine their glucose level on a continuous basis. In order to support blood glucose control through the practical use of these data, database and network plans have been studied for the education, management and treatment of diabetes mellitus. In this study, we fabricated calorie calculation software that can calculate all food-intake calories automatically only by choosing the meal menu in mouse pointing device operation. It was possible for the data to be collected personally, even for elderly persons inexperienced in personal computer operation. In addition, multi-input information can be collected using portable commercial devices such as a blood glucose monitors and metabolic rate monitors. Next, on the basis of three data of blood glucose level, metabolic rate and food intake measured over approximately three months, the tendency for increase and decrease in blood glucose level was estimated based on data mining. As a result, it was shown that the accuracy of estimated variation was improved to 90%, although the error in estimating absolute value is yet large. However, understanding the lifestyles and habits of the patients and selecting appropriate input variables for individuals seems to be more important than extending the data collection period if the objective is to improve estimation accuracy. It was possible to partially clarify the effectiveness of data mining in blood glucose level estimation.
社団法人日本生体医工学会の論文
2003-06-10

データマイニングによる血糖値の変動傾向の推定

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