Diabetes

Systemic Proteome Profiling to Differentiate Primary Glomerular Diseases.

BACKGROUND: Primary glomerulonephritis (GN) is a heterogeneous group of kidney disorders where under...

Technology-enabled insights into SLC transporters in MAFLD: redefining the multi-hit pathogenesis and therapeutic landscape.

Recent advances in structural biology, functional genomics, and artificial intelligence (AI) have ex...

Association between fundus sex index and hypertension, diabetes mellitus, and smoking in the Kumejima study.

Fundus parameters can be used to quantify masculinity or femininity as a fundus sex index (FSI) rang...

Pipeline-optimized machine learning for chronic fatigue syndrome diagnosis: A lightweight, interpretable model using blood biochemical and metabolomic data.

INTRODUCTION AND BACKGROUND: Chronic fatigue syndrome (CFS) is a debilitating multisystem disorder w...

Modeling strategies for CGM data: A scoping review of mechanistic, machine learning, and hybrid approaches in diabetes management.

BACKGROUND: The increasing availability of continuous glucose monitoring (CGM) data has opened new a...

The value of triglyceride-glucose-body shape index (TyG-ABSI) in evaluating stroke: a multi-centre cross-sectional study.

BACKGROUND: Stroke is the second leading cause of disability and mortality worldwide. A body shape i...

Volatilomics insights in older adults with diabetes: from metabolic mechanisms to precision geriatric medicine.

AIMS: This review aims to evaluate the hypothesis that Volatilomics-the comprehensive analysis of vo...

A predictive model for significant periodontal disease progression: A large-scale cohort study.

BACKGROUND: The progression of periodontitis is challenging to predict. This study aimed to develop ...

Real-World Prospective Validation and Economic Evaluation of Deep Learning- Based Diabetic Retinopathy Detection From Fundus Photographs: A Systematic Review and Meta-analysis.

BACKGROUND: Deep learning (DL) has shown promise in delivering diagnostic and economic benefits for ...

Renal interstitial inflammation predicts IgA nephropathy progression via multiple machine learning models.

BACKGROUND: Renal interstitial inflammation (RII) is a frequent pathological feature in IgA nephropa...

Integrated approaches to preventing macrovascular complications in type 2 diabetes mellitus: Advances in secondary prevention.

BACKGROUND: Type 2 diabetes mellitus (T2DM) substantially increases the risk of macrovascular compli...

Retrieval Augmented Generation (RAG) for Evaluating Regulatory Compliance of Drug Information and Clinical Trial Protocols.

The purpose was to evaluate retrieval-augmented generative (RAG) artificial intelligence (AI) method...

Diabetes Spotlight: Martin Myers, MD, PhD-Understanding Metabolism and Glucose Through Neural Networks.

Deep Learning-Enabled Diabetic Retinopathy Screening: A Techno-Clinical Revolution or Just More Artificial Intelligence Hype?

Future-aware blood glucose forecasting using knowledge distillation with transformer-based sequence-to-sequence models.

Accurate blood glucose level (BGL) forecasting is critical for diabetes self-management and clinical...

Predicting Macrophage Spatial Localization from Single-Cell Transcriptomes to Uncover Disease Mechanisms.

When cells are isolated for single-cell RNA sequencing (scRNA-seq), their positional information is ...

Evaluating Accuracy of ChatGPT-4o in Automated Carbohydrate Estimation From Images as a Self-Management Tool for Adolescents With Type 1 Diabetes.

INTRODUCTION: Type 1 diabetes mellitus (T1D) requires precise carbohydrate estimation to manage bloo...

Effectiveness of natural language intelligence technology in chronic diseases nursing: A systematic review and meta-analysis.

BACKGROUND: Chronic diseases pose a heavy global burden, with challenges in utilizing unstructured d...

Deep Learning Model to Detect Diabetic Retinopathy in 45° Images Using Ground Truth from Ultra-Widefield Imaging.

PURPOSE: To evaluate the performance of a deep learning (DL) model in classifying diabetic retinopat...

Adaptive Temporal Mixture of Experts for Predicting Stiffness Metrics from the Ocular Response Analyzer and Identifying Keratoconus: Stiffness Estimates from Ocular Response Analyzer.

PURPOSE: To develop a machine learning-based modeling approach for extracting elastic stiffness esti...

Designing a machine learning model for predicting cardiovascular events using the triglyceride-glucose index: a cohort study.

INTRODUCTION: Cardiovascular diseases (CVD) are the leading cause of death in developing countries, ...