Journal of diabetes science and technology
36629330
BACKGROUND: The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated continuous glucose monitoring (CGM) reduced hypoglycemia over 6 months among older adults with type 1 diabetes (T1D) compared with blood glucose monitor...
Journal of diabetes science and technology
38014538
BACKGROUND: Hypoglycemia is common in insulin-treated type 2 diabetes (T2D) patients, which can lead to decreased quality of life or premature death. Deep learning models offer promise of accurate predictions, but data scarcity poses a challenge. Thi...
Journal of diabetes science and technology
38372235
INTRODUCTION: Continuous glucose monitoring (CGM) is emerging as a transformative tool for helping people with diabetes self-manage their glucose and supporting clinicians in effective treatment. Unfortunately, many CGM users, and clinicians, find in...
The aim of this study was to develop and validate a prediction model based on continuous glucose monitoring (CGM) data to identify a week-to-week risk profile of excessive hypoglycemia. We analyzed, trained, and internally tested two prediction mod...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039424
This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardiograms (ECG) from an extensive database comprising 1119 subjects. Previous research on hyperglycemia or glucose detection using ECG has been constraine...
Technology and health care : official journal of the European Society for Engineering and Medicine
39269871
BACKGROUND: Machine learning offers diverse options for effectively managing blood glucose levels in diabetes patients. Selecting the right ML algorithm is critical given the array of available choices. Integrating data from IoT devices presents prom...
While continuous glucose monitoring (CGM) has revolutionized metabolic health management, widespread adoption remains limited by cost constraints and usage burden, often resulting in interrupted monitoring periods. We propose a deep learning framewor...