Diabetes

Insulin resistance modifies longitudinal multi-omics responses to habitual diet

How habitual diet influences the gut microbiome and plasma metabolome across insulin resistance states remains unclear. We conducted year-long multi-omics profiling of 71 deeply phenotyped adults, integrating repeated assessments of diet, metabolome, gut microbiome, clinical laboratory measures, and inflammatory markers. Using gold-standard insulin suppression tests and machine learning-derived di...

Multi-Model Clinical Validation of an AI-Powered Biomarker Analysis Framework: A Cross-Vendor Benchmark on 4,018 NHANES Patients

Background: Large language models (LLMs) show promise for clinical decision support, yet most validation studies evaluate single models, leaving questions about generalizability and vendor dependence unanswered. We assessed whether a standardized biomarker analysis framework maintains clinical-grade accuracy across multiple LLMs from independent providers. Methods: We developed a structured prompt...

The Stationarity Bias: Stratified Stress-Testing for Time-Series Imputation in Regulated Dynamical Systems

Time-series imputation benchmarks employ uniform random masking and shape-agnostic metrics (MSE, RMSE), implicitly weighting evaluation by regime prev...

CausalCellInfer: Resolving cell-type-specific disease mechanisms from biobank-scale GWAS

Integrating the cellular resolution of single-cell RNA sequencing (scRNA-seq) with the phenotypic depth of population-scale biobanks is essential for ...

Genomics link obesity and type 2 diabetes to Alzheimer's disease to unveil novel biological insights

Body mass index (BMI), type 2 diabetes (T2D) and associated cardiometabolic features modify Alzheimer's disease (AD) risk, yet shared mechanisms remai...

Calibrated Bayesian Deep Learning for Explainable Decision Support Systems Based on Medical Imaging

In critical decision support systems based on medical imaging, the reliability of AI-assisted decision-making is as relevant as predictive accuracy. A...

AI-Driven Clinical Decision Support System for Enhanced Diabetes Diagnosis and Management

Identifying type 2 diabetes mellitus can be challenging, particularly for primary care physicians. Clinical decision support systems incorporating art...

Towards Affordable, Non-Invasive Real-Time Hypoglycemia Detection Using Wearable Sensor Signals

Accurately detecting hypoglycemia without invasive glucose sensors remains a critical challenge in diabetes management, particularly in regions where ...

VFGS-Net: Frequency-Guided State-Space Learning for Topology-Preserving Retinal Vessel Segmentation

Accurate retinal vessel segmentation is a critical prerequisite for quantitative analysis of retinal images and computer-aided diagnosis of vascular d...

Uncertainty-Aware Ordinal Deep Learning for cross-Dataset Diabetic Retinopathy Grading

Diabetes mellitus is a chronic metabolic disorder characterized by persistent hyperglycemia due to insufficient insulin production or impaired insulin...

Assessing extracellular vesicle proteins as predictive biomarkers for developing type 1 diabetes

Plasma extracellular vesicles (EVs) are considered excellent sources for biomarker discovery since they carry signatures of their cellular origin and ...

Context-Aware Asymmetric Ensembling for Interpretable Retinopathy of Prematurity Screening via Active Query and Vascular Attention

Retinopathy of Prematurity (ROP) is among the major causes of preventable childhood blindness. Automated screening remains challenging, primarily due ...

Using Artificial Intelligence to optimize agreement between interstitial sensors and capillary puncture in glycemic assessment and classification

Introduction: Blood glucose monitoring is essential for the management of diabetes mellitus. Continuous interstitial glucose (IG) monitoring systems a...

Performance of Frangi-Hessian Pseudo-Labels for Retinal Vessel Segmentation in AI-Assisted Retinopathy of Prematurity Screening

Background: Retinopathy of prematurity (ROP) is a leading cause of preventable blindness among preterm infants. Accurate retinal vessel segmentation i...

Quasi-multimodal-based pathophysiological feature learning for retinal disease diagnosis

Retinal diseases spanning a broad spectrum can be effectively identified and diagnosed using complementary signals from multimodal data. However, mult...

Decoupling Accuracy and Explainability: Machine Learning Strategies for HbA1c Prediction and Biomarker Discovery in Blood FTIR Spectroscopy

Glycated hemoglobin (HbA1c) is a central biomarker for long-term glycemic control and diabetes management, traditionally quantified using laboratory-i...

Predicting Gene Disease Associations in Type 2 Diabetes Using Machine Learning on Single-Cell RNA-Seq Data

Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels due to impaired insulin production or function. Two main forms...

IGF-like growth factors that couple food sensing to developmental decisions employ different release mechanisms in a single pair of C. elegans chemosensory neurons

Sensory neurons modulate organismal physiology and behavior in part by releasing neuropeptides and neurotrophins or growth factors, via the dense core...

A Mobile AI-enhanced Platform for Standardized Wound Assessment and Clinical Decision Support

Chronic wounds affect over 1.2 million Canadians and incur healthcare costs exceeding $13 billion annually, with global expenditures approaching $149 ...

Experience with Single Domain Generalization in Real World Medical Imaging Deployments

A desirable property of any deployed artificial intelligence is generalization across domains, i.e. data generation distribution under a specific acqu...