Diabetes

The prognostic significance of metabolic score for insulin resistance in evaluating all-cause and cardiovascular mortality risk among individuals across stages 1-4 of cardiovascular-kidney-metabolic syndrome: a nationwide prospective cohort study.

BACKGROUND AND AIM: Cardiovascular-kidney-metabolic syndrome (CKM) embodies the intricate interactio...

Customizing AI-based screening with real-world data: Practical insights from diabetic retinopathy.

PURPOSE: Diabetic retinopathy (DR) is a leading cause of vision loss in middle-aged adults globally....

Improvement of an eye disease detection model by using the denoising diffusion implicit model.

With rapid developments in artificial intelligence (AI), the discussion about and applications of ge...

AI-Driven Fetal Liver Echotexture Analysis: A New Frontier in Predicting Neonatal Insulin Imbalance.

OBJECTIVES: To evaluate the performance of artificial intelligence (AI)-based models in predicting e...

Optimizing guideline-directed medical therapy in chronic kidney disease and type 2 diabetes mellitus patients in primary care.

BACKGROUND: Despite KDIGO (Kidney Disease: Improving Global Outcomes) recommendations for renin-angi...

Detection and quantification of fluorescein angiography leakage: From manual grading to advances in machine learning.

Fluorescein angiography (FA) has long been a cornerstone for evaluating retinal vascular leakage in ...

Exploration and analysis of methylglyoxal-driven chronic inflammation in polycystic ovary syndrome.

INTRODUCTION: Chronic low-grade inflammation drives polycystic ovary syndrome (PCOS)-related metabol...

Letter to the Editor "The role of artificial intelligence in diabetic retinopathy screening in type 1 diabetes: A systematic review".

Flexible wearable medical devices: from material innovations and data processing to intelligent healthcare applications.

BACKGROUND: Flexible wearable medical devices drive healthcare transformation via non-invasive, real...

Proteomic signature of dementia risk in type 2 diabetes.

INTRODUCTION: Type 2 diabetes (T2D) significantly increases dementia risk, yet the molecular mechani...

FTIR spectroscopy imaging coupled with machine learning reveals biochemical changes in the brains of diabetic mice.

Diabetic encephalopathy is a progressive complication of type 2 diabetes, yet its region-specific bi...

Predicting fracture toughness of human cortical bone from donors with and without type 2 diabetes using Raman spectroscopy and machine learning.

Type 2 diabetes mellitus (T2DM) is associated with increased skeletal fragility, yet standard clinic...

Emerging innovations in ophthalmic drug delivery for diabetic retinopathy: a translational perspective.

Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes and a leading caus...

Modification and applications of glucose oxidase: optimization strategies and high-throughput screening technologies.

Glucose oxidase (GOD), an oxidoreductase (EC 1.1.3.4), catalyzes the oxidation of β-D-glucose to glu...

Prediabetes phenotypes: can aetiology and risk profile guide lifestyle strategies for diabetes prevention?

INTRODUCTION: Type 2 diabetes (T2D) continues to worsen globally alongside rise in obesity. Asymptom...

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesi...

Identification and validation of epithelial‑mesenchymal transition‑related genes for diabetic nephropathy by WGCNA and machine learning.

Diabetic nephropathy (DN) is the main cause of end‑stage renal disease, with epithelial‑mesenchymal ...

Development and validation of personalized risk prediction models for patients with IgA nephropathy: a nationwide multicenter cohort study.

BACKGROUND: Effective prediction of immunoglobulin A nephropathy (IgAN) progression is crucial for e...

Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.

OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic ...

Exhaled gas biomarkers: a non-invasive approach for distinguishing diabetes and its complications.

Exhaled gas detection offers a safe, convenient, and non-invasive clinical diagnostic method for pre...

Diabetic retinopathy detection using adaptive deep convolutional neural networks on fundus images.

Diabetic retinopathy (DR) is an age-related macular degeneration eye disease problem that causes pat...