Endocrinology

A novel hybrid transformer-based framework (H-ConvNeXt-Swin) to classify brain tumors using MRI.

This paper introduces a hybrid deep learning model combining ConvNeXt and Swin Transformer for classifying brain tumors from MRI scans. The ConvNeXt backbone is employed to obtain detailed local spatial features, whereas the Swin Transformer identifies hierarchical long-range dependencies, facilitating complementary feature representation. The proposed model is evaluated on a combined public MRI d...

Early Adoption of Autonomous Artificial Intelligence Screening for Diabetic Retinopathy After Introduction of Medicare Billing Code 92229.

PURPOSE: Diabetic retinopathy remains a leading cause of blindness in the United States. Autonomous artificial intelligence (AI) systems for screening have received US Food and Drug Administration authorization, and a dedicated Medicare billing code for autonomous point-of-care retinal screening was introduced in 2021. This study aimed to characterize observed utilization, billing National Provide...

Artificial intelligence in pituitary surgery: the path to clinical solutions.

Artificial intelligence (AI) is rapidly moving from conceptual innovation to high-performing algorithms across the pituitary patient pathway, promisin...

Deep Learning-based Automated Segmentation of Ultra-Widefield Retinal Vasculature for Cardiometabolic Disease Association Analysis.

Retinal vessel analysis in ultra-widefield (UWF) images provides a unique opportunity for large-scale assessment of systemic microvascular health. How...

Integrative Multi-Omics Analysis Identifies Key Molecular Targets Linking Bisphenol A Exposure to Gestational Diabetes Mellitus.

Bisphenol A (BPA) exposure is associated with gestational diabetes mellitus (GDM); however, the underlying molecular mechanisms remain elusive. This s...

Plasma proteomics linking primary and secondary diseases: Insights into molecular mediation from UK Biobank data.

BACKGROUND: Diabetes, hypertension, and dyslipidemia are major risk factors for cardiovascular, neurological, renal, and pulmonary diseases, yet clini...

Hair neuroendocrine signatures of acute stress reaction symptoms: Cross-national validation and latent profile heterogeneity.

The Acute Stress Reaction (ASR) involves transient emotional, somatic, cognitive, and behavioral symptoms after stressful exposure. Acute stress engag...

A machine learning-based framework for predicting type 2 diabetes mellitus using hematological indices.

OBJECTIVE: This study aimed to develop a machine learning (ML) framework to predict incident type 2 diabetes mellitus (T2DM) using routinely available...

Sensitive detection of unopposed estrogen using estrogen receptor functionalized nanoprobes for cancer diagnosis.

Unopposed estrogen refers to prolonged estrogenic stimulation in the absence of adequate progesterone-mediated counter-regulation. Unopposed estrogen ...

Integrative transcriptomics and single-cell analysis identify SIX4 as a candidate epithelial target in ovarian cancer and PCOS-associated ovarian dysregulation.

PURPOSE: Ovarian cancer is a heterogeneous solid tumor, whereas polycystic ovary syndrome (PCOS) is a distinct endocrine-metabolic ovarian disorder. W...

Identification of Activity, Insulin, and Dietary Thresholds Associated With Exercise-Related Hypoglycaemia and Hyperglycaemia in Children With Type 1 Diabetes: A Free-Living Study Using Explainable Machine Learning.

AIMS: Some studies have explored associations between physical activity (PA) and hypoglycaemia in real-life in type 1 diabetes (T1D) but without fully...

Real-Time Anatomy Recognition During Single-Port Retroperitoneal Surgery: A Prospective Comparison Between AI and Operating Surgeon.

BACKGROUND: Real-time anatomical recognition during robot-assisted surgery has the potential to enrich intraoperative decision-making. We made the fir...

Prediction of coronary atherosclerosis progression in type 2 diabetes mellitus based on AI-derived CCTA parameters and clinical factors: a follow-up study.

OBJECTIVE: To develop a predictive model for coronary atherosclerosis progression in patients with type 2 diabetes mellitus (T2DM) based on Artificial...

Accuracy of portable artificial intelligence-supported fundus camera in the screening of diabetic retinopathy in primary care.

OBJECTIVE: Research on the use of portable fundus cameras utilizing artificial intelligence (AI) for diabetic retinopathy (DR) screening in primary ca...

AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.

Purpose To evaluate whether the artificial intelligence (AI)-quantified mean thoracic skeletal muscle (TSM) attenuation from coronary artery calcium (...

Global Diabetes: Rapidly Changing Landscape and a Rising Tide of Opportunities: The 2025 Distinguished International Service in the Cause of Diabetes Award Lecture.

Diabetes affects an estimated 828 million people worldwide; prevalence is growing rapidly in low- and middle-income countries (LMICs), with major heal...

Prediction Model for Mild Cognitive Impairment in Older Chinese Patients With Cerebral Small Vessel Disease Based on XGBoost Algorithms and Shapley Additive Explanations.

OBJECTIVE: This study aims to evaluate cognitive function in patients with Cerebral Small Vessel Disease (CSVD) and investigate its association with v...

Hexagonal Hollow-Core Photonic Crystal Fiber for High-Sensitivity Terahertz Glucose Detection.

Diabetes mellitus is a rapidly escalating global health concern, often leading to severe complications such as neuropathy, vision impairment, vascular...

Recent advances in biomarkers, artificial intelligence, and targeted therapeutic strategies in breast cancer: Current progress and future perspectives.

Breast cancer is a complex and heterogeneous disease that remains a major global health challenge. Recent progress in molecular biology, artificial in...

Baseline biochemical evaluation for etiologic differentiation in ACTH-dependent Cushing's syndrome: machine learning and composite score analysis in a multicenter cohort of 566 patients.

BACKGROUND: Limited availability of corticotropin-releasing hormone (CRH) currently complicates the differentiation of adrenocorticotropin (ACTH)-depe...