The effects of L-carnitine supplementation on glycemic markers in adults: A systematic review and dose-response meta-analysis

M Zamani, N Pahlavani, M Nikbaf-Shandiz… - Frontiers in …, 2023 - frontiersin.org
Background and aims Hyperglycemia and insulin resistance are concerns today worldwide.
Recently, L-carnitine supplementation has been suggested as an effective adjunctive …

Diabetes Management in Transition: Market Insights and Technological Advancements in CGM and Insulin Delivery

TS Yu, S Song, J Yea, KI Jang - Advanced Sensor Research, 2024 - Wiley Online Library
Abstract Continuous Glucose Monitoring (CGM) systems are revolutionizing the real‐time
tracking of blood glucose levels, a cornerstone in effective diabetes management and …

A novel few shot learning derived architecture for long-term HbA1c prediction

M Qaraqe, A Elzein, S Belhaouari, MS Ilam… - Scientific Reports, 2024 - nature.com
Regular monitoring of glycated hemoglobin (HbA1c) levels is important for the proper
management of diabetes. Studies demonstrated that lower levels of HbA1c play an essential …

Internet of Things enabled open source assisted real-time blood glucose monitoring framework

A K. M, R Krishnamoorthy, S Gogula, S Muthu… - Scientific Reports, 2024 - nature.com
Regular monitoring of blood glucose levels is essential for the management of diabetes and
the development of appropriate treatment protocols. The conventional blood glucose (BG) …

A novel BeiDou satellite transmission framework with missing package imputation applied to smart ships

S Liu, D Wu, H Sun, L Zhang - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Obtaining voyage data through a vessel monitoring system (VMS) and transmitting it to a
remote monitoring center through satellites is an important link to realize the information …

HGMLA: A multi-task learning model for assessment of HbA1c and GA levels using short-term CGM sensor data

B Han, Y Wang, X Sun, H Li, J Lu, J Zhou… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Simultaneously assessing glycated hemoglobin (HbA1c) and glycated albumin (GA) levels
provides information on relatively long-term glycemic control over different lengths of time …

A Machine Learning Strategy for Internet-of-Things-Enabled Diabetic Prediction to Mitigate Pneumonia Risk

KM Abubeker, S Baskar - 2022 10th International Conference …, 2022 - ieeexplore.ieee.org
Diabetes has been recently listed as the tenth-largest cause of mortality, accounting for 1.5
million fatalities, and it causes blindness, kidney failure, coronary artery disease, and even …

A deep learning framework for HbA1c levels assessment using short-term continuous glucose monitoring data

B Han, Y Wang, H Li, X Sun, J Zhou, X Yu - Biotechnology and Bioprocess …, 2024 - Springer
Glycated hemoglobin (HbA1c) is a crucial marker for long-term glycemic control, reflecting
cumulative blood glucose history over the past two to three months. Elevated levels of …

[HTML][HTML] Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning …

H Kurasawa, K Waki, T Seki, A Chiba, A Fujino… - JMIR AI, 2024 - ai.jmir.org
Background: Type 2 diabetes (T2D) is a significant global health challenge. Physicians need
to assess whether future glycemic control will be poor on the current trajectory of usual care …

CGM-Based Blood Glucose Prediction Model with LSTM Encoder-Decode Architecture

H Xu, Y Zhang, S Liu, Y Ji, M Lv, P Li - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Accurate prediction of blood glucose levels is crucial for automated treatment in diabetic
patients. This study proposes a blood glucose prediction model based on an improved …