Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning
Original price was: Rs6,500.00.US$64.18Current price is: Rs5,500.00.
PROJ20112 |
Description
Diabetes type 1 is a chronic disease which is increasing at an alarming rate throughout the world. Studies reveal that the complications associated with diabetes can be reduced by proper management of the disease by continuously monitoring and forecasting the blood glucose level of patients. The prior prediction of blood glucose level is necessary to overcome the lag time for insulin absorption in diabetic type 1 patients. We use continuous glucose monitoring (CGM) data to predict future blood glucose level using the previous data points. Our proposed model we are implementing deep learning ANN algorithm improved results for blood glucose level prediction. The feature Extraction method issued at the modality level, and the essential features to improve performance. Ann algorithm give low error value with high prediction result. Root mean square error (RMSE) is used for performance calculation. Meta-Learning Learn from the output of learning algorithms and make a prediction given predictions made by other models.
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