A Plasma glucose prediction tool based on dietary assessment: a case of type 2 diabetes patient

Abstract

Management and control of blood sugar using dietary intervention has for a long time been considered to be important. The caregivers have always advised diabetic patients to moderate the amount of carbohydrates intake. The approach here has always been reduction in the amount of carbohydrates, unfortunately this does not translate to the reduction on the blood sugar in some case. This is explained by the fact that what determines the sugar levels in the blood has to do more with the glycemic load of the carbohydrates consumed which is dependent on the glycemic index of the food item consumed. Though the amount of carbohydrates taken by the patient has a role to play, it is rather indirect. The study, sought to develop a tool for the computation of the glycemic load of the food item consumed by an individual by aggregating the various meals parameters. The tool has been developed by analyzing the dietary factors that affect the glycemic load and using these factors has the regressing variables. The algorithms used in the development of the dietary assessment tool have been used to map and mine the standard glycemic index of individual food item and to estimate individual patient meal item glycemic using regression analysis approach. Experimental data results indicate the tool can compute the glycemic load of the food item which is comparable to the standard glycemic load values and it also gives plasma glucose prediction trajectories which mirrors those obtained from existing clinical trial dataset.