Diabetes

A three-metabolite microbiota-associated signature for early risk stratification of gestational diabetes mellitus.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes and long-term metabolic and cardiovascular risk. However, oral glucose tolerance testing at 24-28 gestational weeks limits early risk stratification. Gut microbiota-associated metabolites may reflect early metabolic abnormalities, including those relevant to cardiometabolic health, but robust early-pregna...

CAMI-DM: Development and validation of a multi-algorithm model for in-hospital mortality risk prediction in diabetic patients with acute myocardial infarction - The China acute myocardial infarction registry.

Patients with diabetes constitute a substantial proportion of those with acute myocardial infarction (AMI) and exhibit distinct pathophysiological characteristics. However, existing guideline-recommended traditional and generic risk prediction models show limited performance in this specific population. Based on the China Acute Myocardial Infarction (CAMI) registry, 6,091 diabetic patients with AM...

Integrative multi-omics analysis identifies VCAN and ESM1 as candidate cell-type-associated biomarkers of NET-related glomerular injury in diabetic kidney disease.

Diabetic kidney disease (DKD) involves complex inflammatory and microvascular injury, but cell-specific molecular signatures linked to neutrophil extr...

Identification of obesity risk factors in 3-12-year-old children and adolescents with prior respiratory tract infections via interpretable machine and deep learning models.

BACKGROUNDS AND OBJECTIVES: Childhood obesity and respiratory tract infections (RTIs) are 2 major global public health issues that frequently co-occur...

A study on risk factors for the progression from T2DM to end-stage renal disease based on Mendelian randomization and logistic regression analysis.

Using two-sample Mendelian randomization (MR) based on GWAS data from the IEU OpenGWAS project and a retrospective clinical cohort, this study investi...

Machine Learning Classification of Prevalent Chronic Disease Using Multidimensional Social, Behavioral, and Psychological Determinants: A Cross-Sectional Analysis of the 2024 National Health Interview Survey.

BACKGROUND: Chronic diseases account for approximately 90% of the $4.5 trillion annual healthcare expenditure in the United States. While traditional ...

Performance of artificial intelligence in diabetes-related foot ulcer detection and assessment: a scoping review of clinical validation studies.

This scoping review synthesized clinical validation evidence of artificial intelligence (AI) algorithms for diabetes-related foot ulcer (DRFU) detecti...

Clinical-guided deep learning framework for diabetic retinopathy: integrating lesion-aware attention, adversarial augmentation, and uncertainty quantification.

The global prevalence of diabetic retinopathy (DR) is increasing in parallel with the rising burden of diabetes, posing a substantial public health ch...

Early Adoption of Autonomous Artificial Intelligence Screening for Diabetic Retinopathy After Introduction of Medicare Billing Code 92229.

PURPOSE: Diabetic retinopathy remains a leading cause of blindness in the United States. Autonomous artificial intelligence (AI) systems for screening...

Beyond the guidelines: Vascular function as the central determinant and therapeutic target in hypertension.

Hypertension has traditionally been defined and managed according to brachial blood pressure levels. Although this pressure-centric strategy has signi...

Integrative Multi-Omics Analysis Identifies Key Molecular Targets Linking Bisphenol A Exposure to Gestational Diabetes Mellitus.

Bisphenol A (BPA) exposure is associated with gestational diabetes mellitus (GDM); however, the underlying molecular mechanisms remain elusive. This s...

Plasma proteomics linking primary and secondary diseases: Insights into molecular mediation from UK Biobank data.

BACKGROUND: Diabetes, hypertension, and dyslipidemia are major risk factors for cardiovascular, neurological, renal, and pulmonary diseases, yet clini...

A machine learning-based framework for predicting type 2 diabetes mellitus using hematological indices.

OBJECTIVE: This study aimed to develop a machine learning (ML) framework to predict incident type 2 diabetes mellitus (T2DM) using routinely available...

Identification of Activity, Insulin, and Dietary Thresholds Associated With Exercise-Related Hypoglycaemia and Hyperglycaemia in Children With Type 1 Diabetes: A Free-Living Study Using Explainable Machine Learning.

AIMS: Some studies have explored associations between physical activity (PA) and hypoglycaemia in real-life in type 1 diabetes (T1D) but without fully...

Leveraging machine learning with real-world data for hypothesis generation by identifying exposomic predictors in Parkinson's disease among farmers.

BackgroundMachine learning offers new avenues for complementing traditional epidemiological approaches by analyzing routinely collected, population-ba...

Prediction of coronary atherosclerosis progression in type 2 diabetes mellitus based on AI-derived CCTA parameters and clinical factors: a follow-up study.

OBJECTIVE: To develop a predictive model for coronary atherosclerosis progression in patients with type 2 diabetes mellitus (T2DM) based on Artificial...

Accuracy of portable artificial intelligence-supported fundus camera in the screening of diabetic retinopathy in primary care.

OBJECTIVE: Research on the use of portable fundus cameras utilizing artificial intelligence (AI) for diabetic retinopathy (DR) screening in primary ca...

AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.

Purpose To evaluate whether the artificial intelligence (AI)-quantified mean thoracic skeletal muscle (TSM) attenuation from coronary artery calcium (...

Global Diabetes: Rapidly Changing Landscape and a Rising Tide of Opportunities: The 2025 Distinguished International Service in the Cause of Diabetes Award Lecture.

Diabetes affects an estimated 828 million people worldwide; prevalence is growing rapidly in low- and middle-income countries (LMICs), with major heal...

Prediction Model for Mild Cognitive Impairment in Older Chinese Patients With Cerebral Small Vessel Disease Based on XGBoost Algorithms and Shapley Additive Explanations.

OBJECTIVE: This study aims to evaluate cognitive function in patients with Cerebral Small Vessel Disease (CSVD) and investigate its association with v...