Diabetes

Statistical Applications in Pediatric Endocrinology: A Simulation on Metformin’s Effect on HbA1c in High-Risk Adolescents

Metformin has been increasingly used off-label in adolescents with type 1 diabetes (T1D) or prediabetic conditions to improve glycemic control. Despite clinical trials suggesting modest improvements in HbA1c, evidence remains mixed and methodologically limited. This paper introduces a simulation framework to evaluate advanced causal inference estimators—including Targeted Maximum Likelihood Estima...

Identification and validation of tolerogenic dendritic cells-related biomarkers in diabetic retinopathy

Diabetic retinopathy (DR) is a primary microvascular complication of diabetes. Its pathogenesis is associated with chronic inflammation and immune responses. While tolerogenic dendritic cells (tolDCs) are critical for suppressing excessive inflammation and maintaining immune homeostasis, their function in DR is not well characterized. This study aims to identify tolDCs-related biomarkers and eluci...

Reinforcement learning optimization of automated insulin delivery in type 1 and type 2 diabetes mellitus

Closed-loop insulin delivery systems have proven effective in regulating blood glucose (BG) concentration, thereby reducing the burden of self-care in...

Classifying the severity of diabetic macular oedema from optical coherence tomography scans using deep learning: a feasibility study

Diabetic macular oedema (DME) is a vision-threatening complication of diabetes mellitus. It is reliably detected using optical coherence tomography (O...

Explainable Deep Learning for Lesion-Level Detection of Diabetic Retinopathy: A Segmentation Approach Using Fundus Images Graded as Mild-to-Moderate Nonproliferative Diabetic Retinopathy

Deep learning has shown promise in diabetic retinopathy screening using fundus images. However, many existing models operate as “black boxes,” providi...

Individualized Therapy Optimization for Type 2 Diabetes

Type 2 diabetes is a wide-spread chronic condition in which blood glucose and body weight management constitute essential therapeutic targets. Emergin...

A Metabolic-Inflammatory Phenotype of Pelvic Floor Dysfunction: A Machine Learning-Based Discovery in a Nationally Representative U.S. Cohort

Pelvic floor dysfunction (PFD) is a highly prevalent and heterogeneous condition among women. The traditional view of PFD as a single clinical entity ...

Discovering latent subtypes of preterm birth and genetic risk using tensor decomposition on electronic health records

Preterm birth is a syndrome that is triggered by diverse biological pathways and presents with many comorbid diseases. Although twin studies reveal a ...

Comparative Mortality Risk of Aripiprazole, Olanzapine, Quetiapine and Risperidone in Alzheimer’s Disease: A Real□World Cohort Study with Treatment Effect Heterogeneity Analysis

Second-generation antipsychotics (SGAs) are frequently used off-label to manage behavioral symptoms in Alzheimer’s disease (AD), despite ongoing conce...

Metformin use is associated with lower mortality from bacterial sepsis and improved immunocompetence in Thai diabetes patients with acute melioidosis

Diabetes mellitus (DM) is a major risk factor for acquiring infections. Metformin, the first-line treatment for type 2 DM, is associated with benefici...

PANCDetect: Early Detection of Pancreatic Cancer from Multimodal EHR data with LLM Embeddings

Pancreatic cancer (PANC) is often diagnosed at late stages due to the absence of specific early symptoms, resulting in one of the highest cancer morta...

BUCAN: Bayesian Uncertainty-aware Classification with Attention Networks for Medical Images

Accurate and reliable medical image classification is critical for clinical decision-making across diverse imaging modalities, including X-ray, CT, an...

Prior knowledge informs graph neural networks to improve phenotype prediction from proteomics

High-throughput proteomics data provides dense individual-level molecular readouts, enabling the development of machine learning models for predicting...

A photoplethysmography-based aging clock reveals genetic determinants of arterial aging

Arterial aging, marked by progressive vascular stiffening, is a contributor to cardiovascular disease. Photoplethysmography (PPG) waveforms offer an e...

Medication-Stratified Analysis of LDL-C Equation Miscalibration in Diabetes: Evidence from the All of Us Research Program and a Medication-Agnostic Machine-Learning Correction

Standard LDL-C equations were derived in cohorts largely untreated with modern combination diabetes therapies. With medication-treated patients compri...

Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but their availability is limited by cost and throughpu...

Comparing different types of machine learning models in diagnosing diabetes mellitus utilizing electrocardiography and clinical data

Diabetes Mellitus (DM) represents one of the most significant global public health challenges of the 21st century. This dramatic increase in the preva...

Ambient Only vs. Longitudinal Data-Enhanced AI Documentation: A Pilot Study Quantifying the Value of Historical Clinical Context in Primary Care

Ambient artificial intelligence (AI) clinical documentation tools have gained rapid adoption in healthcare to address physician burnout from documenta...

Accurate, Race-Free LDL-C Estimation in Non-Fasting Settings: A Machine-Learning Study in 3,477 Adults

Traditional LDL-C testing barriers—mandatory 9–12 hour fasting and inperson visits—disproportionately limit access for rural populations (60% of US co...

Assessment of fatal cardiovascular disease risk using data-driven diabetes subgroups and SCORE2-Diabetes in 24,943 adults in Mexico City

Cardiovascular disease (CVD) is a leading cause of diabetes-related mortality in Mexico. Although diabetes subgroups capture underlying disease hetero...