Diabetes

Construction of an interpretable machine learning model for predicting gestational diabetes mellitus based on 45 dietary nutrients.

Diagnostic Accuracy of Artificial Intelligence-Enabled Retinal Biomarkers for Detecting Type 2 Diabetes and Prediabetes Among Asian Indians [DART Study].

PURPOSE: To identify retinal microvascular features that distinguish normoglycemia from diabetes mellitus (DM)[Study-1] and prediabetes (PreDM)[Study-2] among Asian Indians using artificial intelligence (AI); evaluate their diagnostic accuracy; and examine independent associations of oculomics scores [Oculomic Diabetes Score (ODiS) and Prediabetes Score (OPreS)] with glycemic status. METHODS: We a...

HelixSide: A Comprehensive Method for Local and Global Orientational Analysis of Proteins.

Understanding the relative orientation of protein secondary structure elements is crucial for elucidating their tertiary organization, function, and i...

Machine learning-based LASSO-Cox model for dementia prediction: the role of midlife cardiometabolic, inflammatory, and genetic risk factors in a US cohort.

PURPOSE: We aimed to identify key midlife dementia predictors and develop a novel machine learning (ML) -enabled risk prediction model. METHODS: Using...

Endocrine and metabolic determinants of cardiometabolic risk in mild autonomous cortisol secretion.

BACKGROUND: Benign adrenal tumours, found in 1-7% of adults, can be non-functioning (NFAT) or show mild autonomous cortisol secretion (MACS), i.e., bi...

Deep Learning-Based Prediction of Cardiopulmonary Disease in Retinal Images of Premature Infants.

IMPORTANCE: Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are leading causes of morbidity and mortality in premature infants. OBJEC...

MYO1C is a urinary extracellular vesicle biomarker and mediator of podocyte injury in diabetic nephropathy.

Type 2 diabetic nephropathy (T2DN) is a major complication of type 2 diabetes and a leading cause of chronic kidney disease. This study aimed to explo...

Sleep deprivation and epiretinal membrane risk: Machine learning findings from a nation-wide survey.

PURPOSE: This cross-sectional study explored the association between sleep deprivation and epiretinal membrane (ERM) using machine learning applied to...

How do chronic diseases affect personal and household income? A double debiased machine learning analysis of the China health and retirement longitudinal study (CHARLS) in older adults.

OBJECTIVES: This study aimed to investigate the impacts of chronic diseases such as hypertension, dyslipidaemia and diabetes on personal and household...

The discordance of remnant cholesterol and low-density lipoprotein cholesterol as a predictor of diabetes, diabetic microvascular diseases, and cardiovascular disease.

BACKGROUND: The impact of discordance between remnant cholesterol (RC) and low-density lipoprotein cholesterol (LDL-c) on diabetes, diabetic kidney di...

Machine learning-based prediction of diabetic retinopathy from pupillary abnormalities in a South Indian population.

Diabetic retinopathy (DR) is a common complication of diabetes that can lead to vision loss. Early detection and prevention of DR is crucial to reduce...

Patient-specific deep offline artificial pancreas for blood glucose regulation in type 1 diabetes.

Due to insufficient insulin secretion, patients with type 1 diabetes mellitus (T1DM) are prone to blood glucose fluctuations ranging from hypoglycemia...

Deep learning architectures for modeling and forecasting stroke cases in Ghana.

INTRODUCTION: Stroke remains a leading cause of global morbidity and mortality, ranking second in deaths and third in disability-adjusted life years (...

Cooking and eating quality of ethnic Bora rice (Oryza sativa L.): machine learning-based prediction of resistant starch content in ready-to-eat products.

BACKGROUND: Assamese glutinous Bora rice (Oryza sativa L.) is widely used for various ethnic food preparations. However, its resistant starch (RS) con...

Insights and Advances in Physical Activity Research on Youth with Type 1 Diabetes.

PURPOSE OF REVIEW: Most youth with type 1 diabetes (T1D) do not meet the guidelines for physical activity engagement, thereby diminishing potential be...

The Role of Chemical Engineers in the Pharmaceutical Industry.

Chemical engineers have played a vital role in the pharmaceutical industry for more than a century, bridging the gap between scientific discovery and ...

Quantitative assessment of neonatal health using dried blood spot metabolite profiles and deep learning.

Neonatal prematurity leads to considerable morbidity and mortality, partly because of acquired conditions such as bronchopulmonary dysplasia (BPD), in...

Annotation-free 3D reconstruction and quantification of retinal microvasculature by RADAR.

Three-dimensional mapping of retinal microvasculature is essential for monitoring systemic vascular health. Existing methods rely heavily on manual an...

Quantum denoising autoencoder improves retinal fundus image quality for early diabetic retinopathy screening.

Diabetic Retinopathy (DR) is a critical source of blindness that can be prevented globally, and accurate analysis of retinal fundus images enables ear...

Hemorrhage Segmentation in Fundus Images Using the U-Net 3+ Model: Performance Comparison Across Retinal Regions.

Diabetic retinopathy (DR) is one of the most common complications of diabetes, and timely detection of retinal hemorrhages is essential for preventing...