A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring

Yuting Xing; Hangting Ye; Xiaoyu Zhang; Wei Cao; Shun Zheng; Jiang Bian; Yike Guo

doi:10.1109/BIBM55620.2022.9995522

A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring

Yuting Xing^*, Hangting Ye, Xiaoyu Zhang, Wei Cao, Shun Zheng, Jiang Bian, Yike Guo^*

^*Corresponding author for this work

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Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

4 Citations (Scopus)

Abstract

Continuous glucose monitoring prediction is a crucial yet challenging task in precision medicine. This paper presents a novel neural ODE based approach for predicting continuous glucose monitoring (CGM) levels purely based on sporadic self-monitoring signals. We integrate the expert knowledge from physiological model into our model to improve the accuracy. Experiments on the real-world data demonstrate that our method outperforms other state-of-the-art methods on NRMSE metrics.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022
Editors	Donald Adjeroh, Qi Long, Xinghua Shi, Fei Guo, Xiaohua Hu, Srinivas Aluru, Giri Narasimhan, Jianxin Wang, Mingon Kang, Ananda M. Mondal, Jin Liu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	860-863
Number of pages	4
ISBN (Electronic)	9781665468190
DOIs	https://doi.org/10.1109/BIBM55620.2022.9995522
Publication status	Published - 2022
Event	2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 - Las Vegas, United States Duration: 6 Dec 2022 → 8 Dec 2022

Publication series

Name	Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

Conference

Conference	2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022
Country/Territory	United States
City	Las Vegas
Period	6/12/22 → 8/12/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

blood glucose prediction
diabetes management
neural ODE

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/BIBM55620.2022.9995522

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Xing, Y., Ye, H., Zhang, X., Cao, W., Zheng, S., Bian, J., & Guo, Y. (2022). A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. In D. Adjeroh, Q. Long, X. Shi, F. Guo, X. Hu, S. Aluru, G. Narasimhan, J. Wang, M. Kang, A. M. Mondal, & J. Liu (Eds.), Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 (pp. 860-863). (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM55620.2022.9995522

Xing, Yuting ; Ye, Hangting ; Zhang, Xiaoyu et al. / A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. editor / Donald Adjeroh ; Qi Long ; Xinghua Shi ; Fei Guo ; Xiaohua Hu ; Srinivas Aluru ; Giri Narasimhan ; Jianxin Wang ; Mingon Kang ; Ananda M. Mondal ; Jin Liu. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 860-863 (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022).

@inproceedings{1006c06d091744d0a553c756fe6e3833,

title = "A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring",

abstract = "Continuous glucose monitoring prediction is a crucial yet challenging task in precision medicine. This paper presents a novel neural ODE based approach for predicting continuous glucose monitoring (CGM) levels purely based on sporadic self-monitoring signals. We integrate the expert knowledge from physiological model into our model to improve the accuracy. Experiments on the real-world data demonstrate that our method outperforms other state-of-the-art methods on NRMSE metrics.",

keywords = "blood glucose prediction, diabetes management, neural ODE",

author = "Yuting Xing and Hangting Ye and Xiaoyu Zhang and Wei Cao and Shun Zheng and Jiang Bian and Yike Guo",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 ; Conference date: 06-12-2022 Through 08-12-2022",

year = "2022",

doi = "10.1109/BIBM55620.2022.9995522",

language = "English",

series = "Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "860--863",

editor = "Donald Adjeroh and Qi Long and Xinghua Shi and Fei Guo and Xiaohua Hu and Srinivas Aluru and Giri Narasimhan and Jianxin Wang and Mingon Kang and Mondal, \{Ananda M.\} and Jin Liu",

booktitle = "Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022",

}

Xing, Y, Ye, H, Zhang, X, Cao, W, Zheng, S, Bian, J & Guo, Y 2022, A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. in D Adjeroh, Q Long, X Shi, F Guo, X Hu, S Aluru, G Narasimhan, J Wang, M Kang, AM Mondal & J Liu (eds), Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, Institute of Electrical and Electronics Engineers Inc., pp. 860-863, 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, Las Vegas, United States, 6/12/22. https://doi.org/10.1109/BIBM55620.2022.9995522

A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. / Xing, Yuting; Ye, Hangting; Zhang, Xiaoyu et al.
Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. ed. / Donald Adjeroh; Qi Long; Xinghua Shi; Fei Guo; Xiaohua Hu; Srinivas Aluru; Giri Narasimhan; Jianxin Wang; Mingon Kang; Ananda M. Mondal; Jin Liu. Institute of Electrical and Electronics Engineers Inc., 2022. p. 860-863 (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring

AU - Xing, Yuting

AU - Ye, Hangting

AU - Zhang, Xiaoyu

AU - Cao, Wei

AU - Zheng, Shun

AU - Bian, Jiang

AU - Guo, Yike

PY - 2022

Y1 - 2022

N2 - Continuous glucose monitoring prediction is a crucial yet challenging task in precision medicine. This paper presents a novel neural ODE based approach for predicting continuous glucose monitoring (CGM) levels purely based on sporadic self-monitoring signals. We integrate the expert knowledge from physiological model into our model to improve the accuracy. Experiments on the real-world data demonstrate that our method outperforms other state-of-the-art methods on NRMSE metrics.

AB - Continuous glucose monitoring prediction is a crucial yet challenging task in precision medicine. This paper presents a novel neural ODE based approach for predicting continuous glucose monitoring (CGM) levels purely based on sporadic self-monitoring signals. We integrate the expert knowledge from physiological model into our model to improve the accuracy. Experiments on the real-world data demonstrate that our method outperforms other state-of-the-art methods on NRMSE metrics.

KW - blood glucose prediction

KW - diabetes management

KW - neural ODE

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UR - https://www.scopus.com/pages/publications/85146671487

U2 - 10.1109/BIBM55620.2022.9995522

DO - 10.1109/BIBM55620.2022.9995522

M3 - Conference Paper published in a book

T3 - Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

SP - 860

EP - 863

BT - Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

A2 - Adjeroh, Donald

A2 - Long, Qi

A2 - Shi, Xinghua

A2 - Guo, Fei

A2 - Hu, Xiaohua

A2 - Aluru, Srinivas

A2 - Narasimhan, Giri

A2 - Wang, Jianxin

A2 - Kang, Mingon

A2 - Mondal, Ananda M.

A2 - Liu, Jin

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

Y2 - 6 December 2022 through 8 December 2022

ER -

Xing Y, Ye H, Zhang X, Cao W, Zheng S, Bian J et al. A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. In Adjeroh D, Long Q, Shi X, Guo F, Hu X, Aluru S, Narasimhan G, Wang J, Kang M, Mondal AM, Liu J, editors, Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 860-863. (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022). doi: 10.1109/BIBM55620.2022.9995522

A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring

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Keywords

UN SDGs

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