Short Term Glucose Prediction in Patients with Type 1 Diabetes Mellitus-Reference-Cited by-同舟云学术

Short Term Glucose Prediction in Patients with Type 1 Diabetes Mellitus

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Katsarou Daphne N.¹,Georga Eleni I.¹,Christou Maria²,Tigas Stelios²,Papaloukas Costas¹,Fotiadis Dimitrios I.³

Affiliation:

1. University of Ioannina,Unit of Medical Technology and Intelligent Information Systems,Dept. of Materials Science and Engineering,Ioannina,Greece,GR45110

2. University Hospital of Ioannina,Dept. of Endocrinology,Ioannina,Greece,GR45110

3. Biomedical Research Institute, FORTH, University Campus of Ioannina,Ioannina,Greece,GR45110

Funder

European Regional Development Fund

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09870889.pdf?arnumber=9870889

Reference18 articles.

1. Blood glucose prediction model for type 1 diabetes based on artificial neural network with time-domain features

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

3. Benchmarking Machine Learning Algorithms on Blood Glucose Prediction for Type I Diabetes in Comparison With Classical Time-Series Models

4. Deep Physiological Model for Blood Glucose Prediction in T1DM Patients

5. Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice

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4. Blood Glucose Prediction for Type-1 Diabetics using Deep Reinforcement Learning;2023 IEEE International Conference on Digital Health (ICDH);2023-07