Endocrinology

Evaluating the Intermediate Suspicion Category in Thyroid Nodules with AI Assistance: A Comparative Analysis of C-TIRADS, ACR-TIRADS, and ATA Guidelines.

OBJECTIVE: To compare diagnostic performance and fine-needle aspiration (FNA) decision-making for thyroid nodules classified as "Intermediate Suspicion" across three major ultrasound-based risk stratification systems (2017 ACR-TIRADS, 2015 ATA guidelines, and 2020 C-TIRADS), with and without AI assistance. METHODS: This retrospective study analyzed 1,911 ultrasound images of thyroid nodules from 1...

The Value of Deep Learning in Differentiating Thyroid Adenomatoid Nodules on Ultrasound: A Dual-Center Study.

RATIONALE AND OBJECTIVES: Follicular neoplasms are difficult to classify by ultrasound, as they often present as thyroid adenomatoid nodules (TANU). Furthermore, fine-needle aspiration cytology (FNAC) exhibits limited accuracy in differentiating the nature of follicular lesions. This study aimed to develop and validate a novel model to optimize the workflow for distinguishing benign from malignant...

Integration of hierarchical clustering in hematologic biomarkers prediction for endocrine toxicity during immunotherapy in lung cancer patients.

Immune check-point inhibitors (ICIs) have outstandingly changed the treatment for lung cancer patients providing longer progression-free (PFS) and ove...

Classifying Diabetic and Healthy β-Cells in Type 2 Diabetes Using Machine Learning on Single-Cell RNA Sequencing Data.

Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels due to impaired insulin production or function. Two main forms...

The mediating role of genes in the influence of intestinal flora on type 2 diabetes and the screening of diagnostic markers.

INTRODUCTION: The composition of intestinal flora affects the occurrence and development of type 2 diabetes to some extent, with dysregulation of the ...

Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.

BACKGROUND: Stroke is a major complication of atrial fibrillation (AF), and risk prediction using the congestive heart failure, hypertension, age, dia...

Model-Guided Optimization of a Low-Serum Medium for Madin-Darby Canine Kidney Cells Using a Kolmogorov-Arnold Network and Bayesian Optimization.

Madin-Darby canine kidney (MDCK) cells are important hosts for cell culture-based viral vaccine production, but fetal bovine serum (FBS) supplementati...

Optimized Metabolic Conditions Reveal the Adipogenic Competence of Wharton's Jelly MSCs: Insight from Literature Review and Experimental Validation.

Mesenchymal stromal/stem cells (MSCs) derived from distinct tissue niches exhibit marked functional heterogeneity, yet the determinants governing thei...

The transcriptional landscape in thyroid cancer: current status of circulating biomarkers and liquid biopsy approaches.

INTRODUCTION: Thyroid cancer is the most common endocrine malignancy, and despite advances in understanding its genomic drivers, significant challenge...

Comprehensive multi-omics approach to investigate the association between metabolic syndrome and pituitary neuroendocrine tumor risk in UK biobank: A cohort study.

OBJECTIVE: Metabolic syndrome (MetS) is a cluster of metabolic disorders linked to cancer development and progression. The pituitary gland plays a cen...

Reporting and Data Systems (RADS) in Radiology: The Chinese Experience.

The Reporting and Data Systems (RADS) framework has become a key driver of structured reporting and standardization in radiology. This review summariz...

Bridging Audience Segmentation and Message Intervention: AI-Generated HBM-Based Messages for Diabetes Prevention.

Health communication often faces a segmentation-intervention gap: psychographic segmentation identifies meaningful audience profiles, but these profil...

ANGPTL4 in gestational diabetes: a diagnostic biomarker linked to placental senescence.

Current diagnostic methods for Gestational Diabetes Mellitus (GDM) inadequately reflect early placental pathophysiology. Accelerated cellular senescen...

Correction: Diagnostic performance of machine learning and deep learning algorithms for thyroid cancer metastasis: a systematic review and meta-analysis.

Digital phenotyping of CGM engagement reveals distinct glycemic outcomes.

Benefits from continuous glucose monitors (CGMs) may depend on how devices are used over time-not only how often they are used. We linked one year of ...

E-DCNNBAE: design of a novel segmentation and classification approach for brain tumour prediction.

Context: Health plays an essential role in human life, particularly brain health, which supports vital system functions. Magnetic Resonance Imaging (M...

Effect of cataracts on systemic factor prediction from fundus images.

OBJECTIVE: To evaluate the effect of cataracts on systemic factor predictions from fundus images by comparing predictive values before and after catar...

Impact of a silver filter with deep learning reconstruction on noncontrast abdominopelvic MDCT in terms of image quality, density values and radiation dose reduction.

INTRODUCTION: To assess how the use of a silver beam filtration with deep learning reconstruction (DLR) impacts the unenhanced abdominopelvic CT in te...

Deep Learning-Driven Anticancer Drug Discovery: Emodepside as a Potential Therapeutic Candidate for Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with a poor prognosis. The absence of effective targeted therapies and end...

VN1K is a pangenome-informed multi-omics and phenomics resource for the Vietnamese population.

The population of Vietnam remains underrepresented in global genomic databases. Here, we present VN1K, a resource of multi-omics and phenotypic inform...