Thyroid

Development and evaluation of AI model with deep learning for segmentation of extraocular muscles in thyroid eye disease.

PURPOSE: To develop and evaluate an AI model for the segmentation of extraocular muscles (EOMs) usin...

Microplastics and the Endocrine-Metabolic Interface: Novel Diagnostic Tools Targeting Thyroid-Adipose Axis.

Microplastics (MPs) have been identified as major environmental contaminants that can affect organis...

Prediction and Clinical Application of Central Lymph Node Metastasis in Papillary Thyroid Carcinoma Based on Multi-modal Ultrasound Feature Fusion: A Multi-center Study.

OBJECTIVE: To develop and validate a deep learning model integrating multi-modal ultrasound informat...

Computational fluid dynamics and machine learning modeling of drug delivery by hydroxypropyl methylcellulose.

This study integrates computational fluid dynamics (CFD) simulations with machine learning (ML) mode...

Learning Deep Temporal Representations of Socioeconomic Deprivation.

This study focuses on AI-based quantification of socioeconomic disparities within society. Specifica...

Evaluation of 2D and 3D nnU-Net models with two-label and three-label strategies for automatic segmentation and total metabolic tumor volume estimation of metastatic differentiated thyroid carcinoma on FDG-PET/CT.

PURPOSE: To evaluate the segmentation performance and total metabolic tumor volume (TMTV) prediction...

Explainable AI in Cancer Imaging: Scoping Review of Methods, Modalities, and Clinical Integration.

BACKGROUND: Explainable artificial intelligence (xAI) is increasingly used in medical imaging to enh...

Thyroid disease detection using enhanced extreme learning machine based on drop-connect method.

The long-term physiologic effects of thyroid problems make them one of the most important endocrine ...

Preliminary machine-learning model with clinical, US, and CEUS features for the diagnosis of thyroid follicular-patterned lesions.

BACKGROUND: Though follicular thyroid carcinoma can be confirmed postoperatively by the histological...

Metabolomic profiling of exhaled breath condensate identifies a novel biomarker panel for detecting thyroid and breast cancer.

BACKGROUND: The non-invasive detection of cancer via exhaled breath condensate (EBC) represents a pr...

Remission, Relapse, and Thyroid-Related Parameters Measurement at Discontinuation of Low-Dose Anti-Thyroid Drugs in Graves' Disease.

BACKGROUND: This study aimed to elucidate the relationship between thyroid-related parameters and th...

Transcriptomic sequencing analysis of the tumor microenvironment atlas and potential mechanisms of metastasis in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) is the most prevalent thyroid malignancy and its incidence continu...

Prediction of transient hypocalcemia following total thyroidectomy using machine learning methods.

Combining single cell and bulk transcriptomics with Mendelian randomization identifies gut microbiota related prognostic genes and mechanisms in thyroid cancer.

BACKGROUND: Imbalance in gut microbiota (GM) may play a role in the development of thyroid cancer (T...

Comparative analysis of large language models and clinicians in thyroid eye disease using structured questionnaires.

To preliminarily evaluate agreement between large language models (LLMs) and ophthalmic clinicians r...

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...

Artificial intelligence for predicting transient hypocalcemia after total thyroidectomy.

Transient hypocalcemia is a common complication of total thyroidectomy. This study aimed to evaluate...

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...

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...

MRI-based automated segmentation and multiparametric quantification for assessing orbital soft tissue involvement in thyroid eye disease.

OBJECTIVES: To develop a deep learning-based multimodal framework for automated segmentation of orbi...

Early volume reduction slope as a novel predictor of long-term outcomes following microwave ablation of benign thyroid nodules: a machine learning-enhanced prediction model.

OBJECTIVE: This study aimed to develop and validate a predictive model incorporating early VRR slope...