Artificial intelligence biosensors for continuous glucose monitoring

X **, A Cai, T Xu, X Zhang - Interdisciplinary Materials, 2023 - Wiley Online Library
Artificial intelligence (AI) algorithms in combination with continuous monitoring technologies
have the potential to revolutionize chronic disease management. The recent innovations in …

Glucose transformer: Forecasting glucose level and events of hyperglycemia and hypoglycemia

SM Lee, DY Kim, J Woo - IEEE Journal of Biomedical and …, 2023 - ieeexplore.ieee.org
To avoid the adverse consequences from abrupt increases in blood glucose, diabetic
inpatients should be closely monitored. Using blood glucose data from type 2 diabetes …

[HTML][HTML] Integrating educational theories with virtual reality: enhancing engineering education and VR laboratories

SFA Shah, T Mazhar, T Shahzad, YY Ghadi… - Social Sciences & …, 2024 - Elsevier
Immersive technologies, including virtual reality (VR), augmented reality (AR), mixed reality
(MR), and extended reality (XR), create realistic digital experiences by overlaying digital …

[HTML][HTML] Intelligent control with artificial neural networks for automated insulin delivery systems

JLCB de Farias, WM Bessa - Bioengineering, 2022 - mdpi.com
Type 1 diabetes mellitus is a disease that affects millions of people around the world. Recent
progress in embedded devices has allowed the development of artificial pancreas that can …

T1DiabetesGranada: a longitudinal multi-modal dataset of type 1 diabetes mellitus

C Rodriguez-Leon, MD Aviles-Perez, O Banos… - Scientific Data, 2023 - nature.com
Type 1 diabetes mellitus (T1D) patients face daily difficulties in kee** their blood glucose
levels within appropriate ranges. Several techniques and devices, such as flash glucose …

Evaluation of offline reinforcement learning for blood glucose level control in type 1 diabetes

P Viroonluecha, E Egea-Lopez, J Santa - IEEE Access, 2023 - ieeexplore.ieee.org
Patients with Type 1 diabetes must closely monitor their blood glucose levels and inject
insulin to control them. Automated glucose control methods that remove the need for human …

A deep neural network prediction method for diabetes based on Kendall's correlation coefficient and attention mechanism

X Qi, Y Lu, Y Shi, H Qi, L Ren - Plos one, 2024 - journals.plos.org
Diabetes is a chronic disease, which is characterized by abnormally high blood sugar levels.
It may affect various organs and tissues, and even lead to life-threatening complications …

Platform for precise, personalised glucose forecasting through continuous glucose and physical activity monitoring and deep learning

D Kalita, H Sharma, JK Panda, KB Mirza - Medical Engineering & Physics, 2024 - Elsevier
Emerging research has demonstrated the advantage of continuous glucose monitoring for
use in artificial pancreas and diabetes management in general. Recent studies demonstrate …

[HTML][HTML] Immersive VR for K-12 experiential education–proposing a pedagogies, practicalities, and perspectives informed framework

C Schott, A Milligan, S Marshall - Computers & Education: X Reality, 2024 - Elsevier
Research on immersive virtual reality's (VR) impact on K-12 education, particularly
experiential learning, has increased. However, there is a paucity of research providing …

Efficient nonlinear autoregressive neural network architecture for real-time biomedical applications

B Olney, S Mahmud, R Karam - 2022 IEEE 4th International …, 2022 - ieeexplore.ieee.org
Medical devices, such as continuous glucose monitors (CGMs) and drug-delivery pumps,
are often combined in closed-loop systems for treating chronic diseases. Generally, these …