Endocrinology

SPISE index and ensemble machine learning refine cardiovascular risk stratification in stage 0-3 CKM syndrome.

BACKGROUND: While the single-point insulin sensitivity estimator (SPISE) shows promise as an insulin...

A multi-dimensional computational screening strategy for rapid identification of active components from traditional chinese medicine: Validation and application in Liangdi decoction against endometriosis.

AIMS: This study aims to develop and validate a Multi-Dimensional Computational Screening (MDCS) str...

Molecular basis of precision nutrition: Food components, microbiome-derived metabolites, and multi-omics modeling.

Metabolic disorders, including obesity, type 2 diabetes, metabolic syndrome, and fatty liver disease...

Beyond the Mean: A Machine Learning-Based Trend Analysis of CGM Metrics for Improved HbA1C Estimation in Type 2 Diabetes.

BACKGROUND: Hemoglobin A1C (HbA1C) is the gold standard for assessing long-term glycemic control in ...

Lineage Classification of Pituitary Neuroendocrine Tumors From Whole-Slide Images Using Attention-Guided Graph Representation Learning.

Pituitary neuroendocrine tumors (PitNETs) are common sellar neoplasms and represent a major componen...

Mapping the Research Landscape and Emerging Trends in Hashimoto's Encephalopathy: A CiteSpace-Based Visualization Analysis.

INTRODUCTION: Hashimoto's thyroiditis is the leading cause of hypothyroidism in iodine-sufficient re...

A modular deep learning architecture for interpretable disease prediction across tabular clinical and biometric datasets.

Accurate disease prediction using clinical datasets is essential for improving early diagnosis and c...

Multiple Targets and Pathways Non-Monotonically Regulate Lung Squamous Cell Carcinoma Migration in Response to Phthalates.

Phthalates (PAEs) are widely used plasticizers that are increasingly linked to tumorigenesis. In thi...

Screening for diabetes mellitus in the US population using neural network-based modeling and complex survey designs.

Complex survey designs are widely used in medical cohort studies. Developing risk score models that ...

Deep learning-powered quantification of endocrine cells and CD3+ T cells in the natural history of type 1 diabetes.

AIMS/HYPOTHESIS: Histopathological analysis in type 1 diabetes presents challenges in achieving prec...

Portable Electrochemiluminescence Microarray Sensor for Machine Learning-Assisted Quantitative Analysis of Zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin produced by Fusarium fungi and is widely present in cer...

Integrated multi-omics and single-cell analyses identify metabolic heterogeneity and therapeutic vulnerabilities in medullary thyroid cancer.

BACKGROUND: Medullary thyroid cancer (MTC) is a heterogeneous and aggressive malignancy with limited...

Machine learning-assisted and simulation-based elucidation of phytochemical dipeptidyl peptidase-4 inhibitors towards safer therapeutics for diabetes.

A global problem with Diabetes Mellitus (type 2) is the disruption of insulin release as well as glu...

Dual-mode MXene-based biosensor coupled with machine learning: a smart sensing strategy for detection of zearalenone in food.

BACKGROUND: Zearalenone (ZEN) is a potent endocrine disruptor that poses serious health risks throug...

Multiple machine learning models for the prediction of an early response to radioactive iodine therapy in hyperthyroidism: ablative dose concept.

BACKGROUND: The aim of this novel study was to explore the possibility of the development of a machi...

Cumulative stress hyperglycemia ratio exposure and dynamic trajectories reveal prognostic determinants of acute hyperlipidemic pancreatitis: an 5-year cohort study.

BACKGROUND: The stress hyperglycemia ratio (SHR) and glycemic variability (GV) both reflect acute gl...

Artificial intelligence in ovarian pathophysiology and management: a systematic review and meta-analysis.

BACKGROUND: The integration of artificial intelligence (AI) into reproductive medicine and gynecolog...

Development and validation of a risk prediction model for dysglycaemia at 6-12 weeks postpartum in Chinese women with gestational diabetes: a retrospective cohort study.

BACKGROUND: Compared with normoglycaemic pregnancies, gestational diabetes mellitus (GDM) confers a ...

Prognostic Imaging Biomarkers in Diabetic Macular Edema Treated with Anti-VEGF: A Multicenter AI Perspective.

INTRODUCTION: This study aimed to identify optical coherence tomography (OCT) biomarkers at baseline...

Hyperglycemia-driven metabolic memory signaling destabilizes METTL1 to trigger inflammatory hypertrophy and fibrosis in diabetic cardiomyopathy.

BACKGROUND: Diabetic cardiomyopathy (DCM) occurs in the context of coronary artery disease or pressu...

Reply to the Letter to the Editor: Automated deep learning model for the accurate detection and measurement of adrenal masses in contrast-enhanced abdominal CT.