Although machine learning models are increasingly being developed for clinical decision support for patients with type 2 diabetes, the adoption of these models into clinical practice remains limited. Currently, machine learning (ML) models are being ...
Journal of diabetes science and technology
Mar 31, 2019
BACKGROUND: Many glycemic variability (GV) indices exist in the literature. In previous works, we demonstrated that a set of GV indices, extracted from continuous glucose monitoring (CGM) data, can distinguish between stages of diabetes progression. ...
The human microbiome plays a number of critical roles, impacting almost every aspect of human health and well-being. Conditions in the microbiome have been linked to a number of significant diseases. Additionally, revolutions in sequencing technology...
IEEE journal of biomedical and health informatics
Feb 13, 2019
The diagnosis of type 2 diabetes (T2D) at an early stage has a key role for an adequate T2D integrated management system and patient's follow-up. Recent years have witnessed an increasing amount of available electronic health record (EHR) data and ma...
INTRODUCTION: Diabetic nephropathy is a leading cause of chronic kidney disease (CKD). In diabetes, changes in serum levels of both soluble alpha Klotho (sKL) and fibroblast growth factor 23 (FGF-23) have been associated with CKD progression.
Vitamin D has been considered to regulate calcium and phosphorus homeostasis and to preserve skeletal integrity. Serum 25-hydroxyvitamin D (25(OH)D) is the best indicator of vitamin D levels. The association of serum 25(OH)D deficiency with increased...
Type (II) diabetes is one of the major threats to mankind as it causes insulin resistance in human body and Retinol Binding Protein 4 (RBP4) is currently considered as a potential biomarker for early management of this disease. Hence a low-level dete...
AIM: To evaluate the association of serum FGF21 with subclinical atherosclerosis and pulse wave velocity, a marker of arterial stiffness, in type 2 diabetes Egyptian patients.
An adrenal incidentaloma (AI) is an adrenal mass incidentally found via a radiological modality, independent of an endocrinological investigation. In this review, we aimed to investigate the possible reasons behind the increased frequency in AI detec...