Latest AI and machine learning research in endocrinology for healthcare professionals.
INTRODUCTION: Recent-onset atrial fibrillation (AF) is a common complication of chronic heart failure (CHF), potentially involving both inflammatory and metabolic dysregulation. This study aimed to develop and externally validate an interpretable machine learning (ML) model for predicting recent-onset AF in patients with CHF and to explore the relationships among inflammatory dysregulation, metabo...
In order to accurately identify tumor boundaries and improve diagnostic efficiency, this study proposes a multi-modal tumor boundary identification method based on artificial intelligence virtual cells and saliency near-infrared spectrum imaging, and uses this to construct the "Golden Eyes 3.0" intelligent navigation system. The system integrates the artificial intelligence virtual cell model cons...
PURPOSE: To compare four multimodal large language models (LLMs) with surgeons on the 2023 Japanese Surgical Specialist Examination using item-level s...
Adolescent major depressive disorder (MDD) is a heterogeneous disorder that complicates diagnosis and treatment. However, the mechanisms underlying th...
Allergic rhinitis (AR) is a prevalent inflammatory disorder of the upper airways, and exposure to environmental endocrine-disrupting chemicals such as...
Diabetes mellitus (DM), a highly prevalent metabolic disorder, is increasingly recognised for its significant association with glaucoma, a leading cau...
To develop and internally validate a multimodal ultrasound-based decision support framework for benign-malignant risk stratification of Bethesda IV th...
Saliva has emerged as a compelling liquid biopsy for the non-invasive diagnosis and monitoring of both oral and systemic diseases. Secreted by major a...
To characterize global trends in ophthalmic AI research from 2015-2025 and drive transferable insights into the broader evolution of AI in medicine, w...
Automated ultrasound image classification is increasingly important for clinical decision support in breast, thyroid and fetal screening. However, dep...
AIMS: Intramuscular fat (IMF) is increasingly recognized as a marker of ectopic adiposity and adverse cardiometabolic outcomes. Artificial intelligenc...
OBJECTIVES: We adapted the individualized polysocial risk score (iPsRS), a machine learning model originally developed for patients with type 2 diabet...
Current antiresorptive therapies reduce bone loss by eliminating osteoclasts or inhibiting their formation. However, these approaches could disrupt os...
BACKGROUND: Post-operative delirium is a serious neurocognitive complication of cardiac surgery. The stress hyperglycaemia ratio (SHR), which adjusts ...
Inverse design of terahertz (THz) metasurfaces via algorithmic models has become a mainstream trend and finds wide application in THz biosensing devic...
PURPOSE: Diabetic retinopathy (DR) screening is essential to prevent vision loss, yet rising diabetes prevalence threatens to outpace ophthalmology ca...
Gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), preterm birth, and intrauterine growth restriction represent major con...
BACKGROUND: Prognosis remains heterogeneous among critically ill patients with acute kidney injury (AKI). We evaluated the triglyceride-glucose frailt...
BACKGROUND: Multimodal large language models (LLMs) are increasingly being explored for medical image analysis, but their relative performance in thyr...
OBJECTIVE: This study aimed to evaluate the structural characteristics of mandibular alveolar bone in patients with Type 1 diabetes mellitus (T1DM), T...