Stacked LSTM based deep recurrent neural network with kalman smoothing for blood glucose prediction

Stacked LSTM based deep recurrent neural network with kalman smoothing for blood glucose prediction

Abstract Background Blood glucose (BG) management is crucial for type-1 diabetes patients resulting in the necessity of reliable artificial pancreas or insulin infusion systems. In recent years, deep learning techniques have been utilized for a more accurate BG level prediction system. However, cont...

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Bibliographic Details
Main Authors: Md Fazle Rabby, Yazhou Tu, Md Imran Hossen, Insup Lee, Anthony S. Maida, Xiali Hei
Format: Article
Language:English
Published: BMC 2021-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Blood glucose level prediction
Recurrent neural network
Stacked long short-term memory
Sensor fault correction
Kalman smoothing
Online Access:https://doi.org/10.1186/s12911-021-01462-5

Internet

https://doi.org/10.1186/s12911-021-01462-5

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