Blood Glucose Prediction Using RNN, LSTM, and GRU: A Comparative Study-Reference-Cited by-同舟云学术

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Blood Glucose Prediction Using RNN, LSTM, and GRU: A Comparative Study

Published:2024-04-27 Issue: Volume:4 Page:1-5
ISSN:
Container-title:2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)
language:
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Author:

Alshehri Osama S.¹,Alshehri Osama M.²,Samma Hussein³

Affiliation:

1. King Fahd University of Petroleum and Minerals,Electrical Engineering Department,Dhahran,Saudi Arabia

2. King Fahd University of Petroleum and Minerals,Mechanical Engineering Department,Dhahran,Saudi Arabia

3. SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRC-AI), King Fahd University of Petroleum and Minerals,Dhahran,Saudi Arabia

Funder

KFUPM

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10596138/10596139/10596176.pdf?arnumber=10596176

Reference11 articles.

1. Online Glucose Prediction Using Computationally Efficient Sparse Kernel Filtering Algorithms in Type-1 Diabetes

2. A review of personalized blood glucose prediction strategies for T1DM patients

3. Predicting Blood Glucose Levels with EMD and LSTM Based CGM Data

4. A Multi-Patient Data-Driven Approach to Blood Glucose Prediction

5. Blood glucose prediction with variance estimation using recurrent neural networks;John;J Healthcare Inf Res,2020

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