A Comparative Study of Time Series Models for Blood Glucose Prediction-Reference-Cited by-同舟云学术

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A Comparative Study of Time Series Models for Blood Glucose Prediction

Published:2022-08-04 Issue: Volume: Page:81-91
ISSN:2524-7565
Container-title:Proceedings of the Third International Conference on Information Management and Machine Intelligence
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Author:

Goel Sofia,Sharma Sudhansh

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2065-3_11

Reference19 articles.

1. Zhu T, Kuang L, Li K, Zeng J, Herrero P, Georgiou P (2021) Blood glucose prediction in type 1 diabetes using deep learning on the edge. In: 2021 IEEE international symposium on circuits and systems (ISCAS), IEEE, pp 1–5

2. Sparacino G, Zanderigo F, Corazza S, Maran A, Facchinetti A, Cobelli C (2007) Glucose concentration can be predicted ahead in time from continuous glucose monitoring sensor time-series. IEEE Trans Biomed Eng 54(5):931–937

3. Deutsch T, Lehmann ED, Carson ER, Roudsari AV, Hopkins KD, Sönksen PH (1994) Time series analysis and control of blood glucose levels in diabetic patients. Comput Methods Prthograms Biomed 41(3–4):167–182

4. Martinsson J, Schliep A, Eliasson B, Mogren O (2020) Blood glucose prediction with variance estimation using recurrent neural networks. J Healthc Inform Res 4(1):1–18

5. Sun Q, Jankovic MV, Bally L, Mougiakakou SG (2018) Predicting blood glucose with an LSTM and bi-LSTM based deep neural network. In: 2018 14th symposium on neural networks and applications (NEUREL), IEEE, pp 1–5

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