… We review that deep learning methods do that extricating task very … of diabetes and HRV
signal variations in the most accurate and fast manner. We discuss several deep learning …

… a deep learning model (DLM) to estimate HbA1c via ECG. Methods: there were 104,823 ECGs
with … which were utilized to train a DLM for calculating ECG-HbA1c. Next, 1539 cases from …

… diabetes. This research paper presents a methodology for classification of diabetic and normal
HRV signals using deep learning … clinicians to diagnose diabetes using ECG signals with …

… [32] monitored the ECG and blood glucose concentration of 9 type-1 diabetic children by
using a Holter and continuous glucose monitoring device. They also identified a prolongation of …

… ECG with the power of machine learning to detect diabetes … processing to predict diabetes,16
using deep learning (DL) … rate signals in diabetes detection,17 ECG-based detection of …

… Our results showed that leveraging deep learning methodologies for the analysis of ECG in
… that might help individuals, especially diabetic patients to better control their blood glucose …

… score of diabetes for every patient, which is further used for classifying patients into diabetic
and nondiabetic. … based detection of Hypoglycemic events using ECG signals. Robert et. al. …

… ECGs to conduct prospective studies of IFG, diabetes, and the development of IFG into …
of deep learning for diagnoses from human ECGs; this requires only a 5-second 12-lead ECG …

… We do believe that an extensive review on PPG and ECG signals analysis in diabetes care
… In this section, we present the deep learning approaches to detect diabetes, estimate blood …

… ECG and heart rate variability (HRV) signals. In [16], authors investigated the
applications of deep learning for the detection of diabetic patients. Deep learning and ECG-based …