Latest AI and machine learning research in endocrinology for healthcare professionals.
INTRODUCTION: The integration of artificial intelligence (AI) tools into medical education presents new opportunities for enhancing students' research skills and scientific writing. However, concerns remain about the potential for cognitive disengagement and the ethical use of AI when lacking appropriate educational supervision. This study aimed to evaluate a novel educational strategy combining s...
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, clini...
The escalating release of emerging organic contaminants into aquatic systems necessitates rigorous investigation of their reactivity with chlorine, a ...
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 ...
Fermentation is driven by dynamic interactions between substrates and microbial communities. However, the complexity of natural consortia limits their...
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...
PURPOSE: With the rising prevalence of obesity and metabolic syndrome, there is an increasing need for noninvasive quantification of pancreatic fat as...
Thyroid-associated ophthalmopathy (TAO), the most common orbital disease in adults, is a specific autoimmune condition closely associated with thyroid...