Endocrinology

Latest AI and machine learning research in endocrinology for healthcare professionals.

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Morphological and Functional Alterations in Type 2 Diabetes Pancreata assessed with MRI-based metrics and [18F]FP-(+)-DTBZ PET

To determine if combining PET-derived beta-cell mass (BCM) estimates with MRI- based morphology metr...

Dietary Macronutrient Intake and the Gut Microbiome in Adults Undergoing Bariatric Surgery for Obesity

Limited information linking dietary intake to gut metagenomic data in bariatric surgery patients is ...

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 prediabe...

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) concentr...

Individualized Therapy Optimization for Type 2 Diabetes

Type 2 diabetes is a wide-spread chronic condition in which blood glucose and body weight management...

An Explainable Hybrid CNN–Transformer Framework with Aquila Optimization for MRI-Based Brain Tumor Classification

Accurate and interpretable brain tumor classification remains a critical challenge due to the hetero...

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 ...

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

High-throughput proteomics data provides dense individual-level molecular readouts, enabling the dev...

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 t...

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...

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—disproportionatel...

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 di...

Incorporating Dietary Information to Enhance Polygenic Prediction Models with Applications to Body Mass Index and Type 2 Diabetes

Polygenic predictors can enhance screening for biomedical conditions, such as metabolism-related tra...

A Tabular Residual Neural Network for Diabetes Classification and Prediction

Diabetes Mellitus (DM) is a metabolic disorder characterized by hyperglycemia, with type 1 character...

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