Diabetes

Evaluating the accuracy and consistency of ChatGPT for the management of type 2 diabetes: A cross-sectional study

Large language models (LLMs) have fundamentally changed how patients and clinicians retrieve information; however, it is unclear how accurate and consistent widely available LLMs are in answering questions related to medical information. Our objective was to evaluate the accuracy and consistency of ChatGPT in answering questions related to the management of type 2 diabetes mellitus (T2DM). Three u...

Comparative Analysis of Long COVID and Post-Vaccination Syndrome: A Cross-Sectional Study of Clinical Symptoms and Machine Learning-Based Differentiation

Long COVID is a well-documented post-viral syndrome, while post-vaccination syndrome (PVS) remains poorly characterized. Understanding their similarities and differences is essential for refining diagnostic criteria and developing targeted interventions. This study systematically compares the symptomatology of long COVID and PVS following COVID-19 vaccination, highlighting key distinctions that co...

Artificial Intelligence quantified prostate specific membrane antigen imaging in metastatic castrate-resistant prostate cancer patients treated with Lutetium-177-PSMA-617

The VISION study1 found that Lutetium-177 (177Lu)–PSMA-617 (“Lu-177”) improved overall survival in metastatic castrate resistant prostate cancer (mCRP...

From Evidence to Data Framework: Decision Factors and Structured Data for AI-Driven Clinical Decision Support Systems in Offloading Footwear

Diabetes-related foot ulcers (DFUs) are a serious complication of diabetes, often resulting in infection, amputation, or even mortality. Offloading fo...

Beyond Accuracy in Small Open-Source Medical Large Language Models for Pediatric Endocrinology

Small open-source medical large language models (LLMs) offer promising opportunities for low-resource deployment and broader accessibility. However, t...

A Comprehensive Approach to Days’ Supply Estimation in a Real-World Prescription Database: Data Cleaning, Imputation, and Adherence Analysis

For accurate medication usage statistics and medication adherence calculations, we need to have an accurate days’ supply (DS) for each prescription. U...

Enhanced Diabetes Prediction Using Novel Additive-Multiplicative Neural Networks: A Comprehensive Machine Learning Analysis of the PIMA Indians Dataset

Early diabetes detection remains challenging, requiring robust machine learning approaches that balance accuracy with clinical interpretability for ef...

Deep learning-based prediction of cardiopulmonary disease in retinal images of premature infants

Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are leading causes of morbidity and mortality in premature infants. To determine whet...

ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care

Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse be...

Plasma Proteomics Linking Primary and Secondary diseases: Insights into Molecular Mediation from UK Biobank Data

Diabetes, hypertension, and dyslipidemia are major risk factors for cardiovascular (CVD), cerebral, and renal diseases (RD). However, the underlying m...

DDR-Augmented-Artifacts: Synthetic Artifact Overlays for Robust Diabetic Retinopathy Models

Deep learning models for the screening of diabetic retinopathy (DR) have achieved near-human performance on benchmark datasets, but their performance ...

Early Prediction of Gestational Diabetes Using Integrated Cell-free DNA Features and Omics-derived Genetic Scores

Gestational diabetes mellitus (GDM) affects 15.6% of pregnancies globally, with Vietnam exhibiting one of the highest prevalences at 21%. Current diag...

Internal and External Validation of Machine Learning Algorithms Versus FINDRISC for Incident Type 2 Diabetes: A Transparent, Explainable Benchmark Using SHAP

Type 2 diabetes mellitus (T2DM) affects almost half a billion people, and the projected cost is $2.25 trillion by 2030; early detection strategies are...

Individualized treatment effects of corticosteroids in IgA nephropathy

IgA nephropathy (IgAN) is a leading cause of kidney failure with diverse clinical presentations and treatment responses, particularly to corticosteroi...

Deep Learning-Identified Clinical Trajectory Patterns and Associations with Kidney Outcomes in IgA Nephropathy

The heterogeneous course of IgA nephropathy limits risk stratification based on static markers. We sought to identify clinical trajectory subgroups us...

Pre-trained Vision Transformer With Masked Autoencoder for Automated Diabetic Macular Edema Detection from Optical Coherence Tomography Images

To develop and evaluate a novel self-supervised learning approach using Masked Autoencoder (MAE) pre-trained Vision Transformer (ViT) for automated de...

Development of Machine Learning Models to Predict Hypoglycemia and Hyperglycemia on Days of Hemodialysis in Patients with Diabetes based on Continuous Glucose Monitoring

Patients with diabetes undergoing hemodialysis (HD) are at risk of asymptomatic hypo- and hypergly-cemia within 24 hours of dialysis. Continuous gluco...

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 metrics improves the prediction of beta-cell functiona...

BASIC: Bayesian Spiral Attention Classifier for Interpretable Medical Image Classification

Accurate medical image classification is critical for early diagnosis and effective treatment planning. However, conventional deep learning models oft...

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 available. We examined whether there were correlat...