Latest AI and machine learning research in diabetes for healthcare professionals.
Type-2 diabetes is a major public health concern in Bangladesh, and this dataset provides 1065 curated patient records with demographic, anthropometric, and clinical variables relevant to its assessment. The data were collected during routine clinical visits and recorded by trained staff, with checks to ensure accuracy and completeness. It includes basic details like age, pregnancy count, body mas...
BACKGROUND: Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, arising from complex interactions among demographic, clinical, behavioral, and social determinants. Leveraging large, nationally representative datasets such as the 2022 Behavioral Risk Factor Surveillance System (BRFSS) offers a unique opportunity to identify emerging risk patterns, monitor population-leve...
BACKGROUND: Alzheimer's disease (AD) is increasingly recognized as a multifactorial network disorder in which amyloid and tau pathology interact with ...
BACKGROUND AND OBJECTIVE: Insulin sensitivity prediction is crucial for model-based treatment in Intensive Care Unit patients, particularly those with...
Insulin signaling is vital for cellular homeostasis, with dysregulation leading to severe metabolic disorders, particularly diabetes. While insulin an...
BACKGROUND: Insulin resistance (IR) indices like the TyG index are predictors of type 2 diabetes (T2DM), but their comparative performance across BMI ...
BACKGROUND: Machine learning (ML) may improve prediction of atrial fibrillation (AF), but its value compared with traditional models such as Cohorts f...
Glucose mutarotation plays a fundamental role in carbohydrate chemistry by governing the interconversion between Ī±- and Ī²-anomers in solution, thereby...
BACKGROUND AND AIMS: A limited amount of diabetic retinopathy (DR) development can be explained by traditional risk factors. This study aimed to deter...
Healthcare decision-making requires not only accurate predictions but also insights into how factors influence patient outcomes. While traditional mac...
Peroxisome proliferator-activated receptor Ī³ (PPARĪ³) is a key therapeutic target for type 2 diabetes and cardiovascular diseases due to its central ro...
PURPOSE: To evaluate the performance of a customized deep learning algorithm for automated segmentation of nonperfusion area (NPA) on ultra-widefield ...
BACKGROUND: The pathological process of atherosclerotic cardiovascular disease (ASCVD) involves complex interactions between metabolic dysregulation a...
BACKGROUND: This study was conducted to examine the effects of eHealth and artificial intelligence literacy on disease self-management in patients wit...
BACKGROUND AND OBJECTIVE: Growth hormone deficiency (GHD) and idiopathic central precocious puberty (ICPP) are typically diagnosed through invasive st...
Malto-oligosaccharides, structurally diverse glucose polymers comprising 2-10 monosaccharide units, play vital roles in food science, pharmaceuticals,...
Type 2 diabetes mellitus (T2DM) is a global disease threatening human health. Regulating blood glucose homeostasis is a key strategy for the treatment...
Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder closely associated with oxidative stress. Natural source polysaccharides (NSPs) show...
This study proposes a transfer learning framework for non-invasive glucose prediction using diffuse-reflectance near-infrared (NIR) spectroscopy, alon...
ADP-glucose pyrophosphorylase (AGPase; E.C. 2.7.7.27) is the rate-limiting enzyme catalyzing the first committed step of starch biosynthesis in higher...