Mobile Software Development Kit for Real Time Multivariate Blood Glucose Prediction-Reference-Cited by-同舟云学术

Mobile Software Development Kit for Real Time Multivariate Blood Glucose Prediction

Published:2024 Issue: Volume:12 Page:5910-5919
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Wolff Miriam K.¹^ORCID,Schaathun Hans Georg¹,Fougner Anders Lyngvi²^ORCID,Steinert Martin³^ORCID,Volden Rune¹^ORCID

Affiliation:

1. Department of Information and Communications Technology (ICT) and Natural Sciences, Norwegian University of Science and Technology, Ålesund, Norway

2. Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway

3. Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Norway

Funder

Department of Information and Communications Technology (ICT) and Natural Sciences, Norwegian University of Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10379644.pdf?arnumber=10379644

Reference37 articles.

1. Glucotypes reveal new patterns of glucose dysregulation

2. Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes

3. Advances in Artificial Pancreas Systems

4. Cambios glucémicos durante el ciclo menstrual en mujeres con diabetes mellitus tipo 1

5. Consumer Wearables and Affective Computing for Wellbeing Support

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1. Continuous glucose monitoring using machine learning models and IoT device data: A meta-analysis;Technology and Health Care;2024-08-29

2. Real-Time Blood Glucose Prediction Reveals a Discrepancy Between Performance Metrics and Real-World Evaluations;2024 IEEE International Conference on Real-time Computing and Robotics (RCAR);2024-06-24