Endocrinology

Correction: ThyroFusion: A Multi-modal Deep Learning Framework Integrating Vision and Language for Thyroid Nodule Malignancy Risk Assessment.

Classification of glucose profile in Japanese patients with type 1 diabetes and its association with complications.

CONTEXT: The importance of utilizing continuous glucose monitoring (CGM) to optimize glycemic profiles and thereby prevent the onset of diabetic complications in patients with type 1 diabetes has been increasingly recognized. Nevertheless, studies evaluating the risk of diabetic complications in patients with type 1 diabetes through machine learning approaches based on CGM data remain limited. OBJ...

Separable, nonlinear, and interactive effects of testosterone and cortisol during status competition in humans: Evidence for the context-dependent dual hormone hypothesis.

The Dual Hormone Hypothesis is a biosocial model that describes the interactive effects of testosterone and cortisol on status-relevant behavior. Unde...

The atlas of abdominal organ remodeling in hepatocellular carcinoma patients: An artificial intelligence-based multicenter imaging study.

BACKGROUND: Morphological changes of abdominal organs in hepatocellular carcinoma (HCC) remain uncharacterized. This study aimed to automatically quan...

A body roundness index (BRI)-based predictive model for metabolic syndrome in perimenopausal and postmenopausal women-from a cross-sectional machine learning study to a longitudinal dynamic assessment.

BACKGROUND AND AIMS: Metabolic syndrome (MetS) is highly prevalent among perimenopausal and postmenopausal women and poses a major public health chall...

Machine Learning Surface Plasmon Resonance Biosensor for Simultaneous Detection of Glucose and Plasmodium falciparum Biomarkers.

In low-resource clinical settings, Plasmodium falciparum infection and hypoglycemia frequently co-present yet require discrete diagnostic platforms, c...

Improving Precision Diagnosis and Treatment of Diabetes in Low-Resource Settings in Africa Through Structured Clinical Phenotyping: A Narrative Review.

Precision diabetes care is an evolving evidence-based, personalised approach that uses an individual's clinical, metabolic, and genetic data to accura...

Proteomic clocks combined with deep learning phenotypes track eye aging and diseases.

Proteomics represents a powerful but underutilized approach for characterizing eye aging. Here, leveraging data from three large-scale, cross-national...

Cross-population validation of the TyG-ABSI index as a novel predictor for chronic obstructive pulmonary disease: an integrated analysis using logistic regression and explainable machine learning.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is increasingly recognized as a systemic inflammatory condition closely linked to metabolic d...

Association of the CHG Index with the onset, progression, and prognosis of cardiovascular-kidney-metabolic syndrome: findings from two large prospective cohorts.

BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome represents a composite disease state driven by glucose and lipid metabolic dysregulation. T...

Predicting and explaining poor prognosis in diabetic kidney disease using SHAP-based interpretable machine learning.

Prognostic assessment of diabetic kidney disease (DKD) is essential for personalized management. This study developed eight machine learning models us...

Clinical Implications and Research Progress of Salivary Biomarkers for Endocrine and Metabolic Disorders.

AIMS: Similar to blood, saliva contains a broad range of biomarkers and may offer a non-invasive, repeatable specimen for endocrine and metabolic asse...

Radiomics in thyroid nodule assessment.

This narrative review was conducted by searching PubMed and Google Scholar using keywords such as 'radiomics' AND 'thyroid nodules' from March 2019 to...

DEHP-induced male reproductive toxicity: Evidence from population studies, animal experiments, and multi-omics profiling.

OBJECTIVE: To evaluate the association between di(2-ethylhexyl) phthalate (DEHP) exposure and testosterone deficiency in adult men, and to explore mol...

Patient-specific modeling identifies metabolic interventions for reversing glucose use reprogramming in alcohol-associated hepatitis.

Alcoholic hepatitis (AH) is an acute form of alcohol-associated liver disease with very few treatment options. Recent studies highlighted liver metabo...

Federated MobileNetV2 with ensemble meta-learning for privacy-preserving brain tumor classification.

The identification of brain tumors from MRI images is very crucial for the selection of an appropriate treatment. However, the existing solution has i...

Multi-omics biomarkers in endometrial receptivity: from mechanisms to clinical translation.

BACKGROUND: Endometrial receptivity (ER) serves as a critical determinant for successful embryo implantation, yet its molecular complexity and limited...

Single-cell-based analysis establishes C1QA-mediated promotion of high glucose-induced tubular epithelial injury via ERS in DN.

BACKGROUND: Diabetic nephropathy (DN) poses a growing worldwide health challenge as a leading cause of end-stage renal disease, a condition that arise...

Nutritional Characteristics of Foods With Addictive Potential: A Machine-Learning Approach.

Objectives. To identify nutritional characteristics associated with the perceived addictive potential of commonly consumed foods in the US food supply...

Agreement between three state-of-the-art deep learning bone age estimation models and chronological age in a large contemporary pediatric cohort.

BACKGROUND: Radiographic bone age estimation is routinely performed in children to evaluate short stature, early or late puberty, and endocrine disord...