Thyroid

Comprehensive framework for thyroid disorder diagnosis: Integrating advanced feature selection, genetic algorithms, and machine learning for enhanced accuracy and other performance matrices.

Thyroid hormones control crucial physiological activities, such as metabolism, oxidative stress, ery...

Impact of Field-of-view Zooming and Segmentation Batches on Radiomics Features Reproducibility and Machine Learning Performance in Thyroid Scintigraphy.

BACKGROUND: Thyroid diseases are the second most common hormonal disorders, necessitating accurate d...

When the Slide Knows the Sequence: Artificial Intelligence-Assisted Pathology Predicts Mutations in Thyroid Cancer.

Interpretable deep fuzzy network-aided detection of central lymph node metastasis status in papillary thyroid carcinoma.

PURPOSE: The non-invasive assessment of central lymph node metastasis (CLNM) in patients with papill...

Multi-omics analysis unveils dysregulation of the tumor immune microenvironment and development of a machine learning-based multi-gene classifier for predicting lateral lymph node metastasis in papillary thyroid carcinoma.

PURPOSE: Lateral lymph node metastasis (LNM) critically influences surgical decision-making in papil...

Predictive Modelling Using Thyroid Cartilage Segmentation and Radiomic Features: A Feasibility Study.

UNLABELLED: Laryngeal cancer, one of the top three head and neck cancers, requires timely diagnosis ...

Identification of stemness subtypes and prognostic modeling in thyroid cancer: the critical role of DPYSL3 in tumor progression and immune microenvironment.

PURPOSE: The objective of this study was to develop and evaluate a novel classifier and prognostic m...

Preoperative Identification of Papillary Thyroid Carcinoma Subtypes and Lymph Node Metastasis via Deep Learning-Assisted Surface-Enhanced Raman Spectroscopy.

Accurate preoperative diagnosis of papillary thyroid carcinoma (PTC) histological subtypes and lymph...

A Deep Learning-Based Artificial Intelligence Model Assisting Thyroid Nodule Diagnosis and Management: Pilot Results for Evaluating Thyroid Malignancy in Pediatric Cohorts.

Artificial intelligence (AI) models have shown promise in predicting malignant thyroid nodules in a...

Application research of artificial intelligence software in the analysis of thyroid nodule ultrasound image characteristics.

Thyroid nodule, as a common clinical endocrine disease, has become increasingly prevalent worldwide....

Combining structural equation modeling analysis with machine learning for early malignancy detection in Bethesda Category III thyroid nodules.

Atypia of Undetermined Significance (AUS), classified as Category III in the Bethesda Thyroid Cytopa...

Multi-Omics-Based Characterization of DNA Methylation Episignatures for Papillary Thyroid Cancer in a Chinese Population.

Thyroid cancer is the most common endocrine malignancy, with papillary thyroid cancer (PTC) account...

Integrative transcriptomics and single-cell transcriptomics analyses reveal potential biomarkers and mechanisms of action in papillary thyroid carcinoma.

OBJECTIVE: Papillary thyroid carcinoma (PTC) has a high recurrence rate and lacks reliable diagnosti...

A protein-based classifier for differentiating follicular thyroid adenoma and carcinoma.

Differentiating follicular thyroid adenoma (FTA) from carcinoma (FTC) remains challenging due to sim...

Explainable Deep Learning System for Automatic Detection of Thyroid Eye Disease using Facial Images.

PURPOSE: To report an explainable deep learning (XDL) system to automatically detect thyroid eye dis...

AI-based multimodal prediction of lymph node metastasis and capsular invasion in cT1N0M0 papillary thyroid carcinoma.

BACKGROUND: Accurate preoperative evaluation of cT1N0M0 papillary thyroid carcinoma (PTC) is essenti...

Deep learning model for malignancy prediction of TI-RADS 4 thyroid nodules with high-risk characteristics using multimodal ultrasound: A multicentre study.

The automatic screening of thyroid nodules using computer-aided diagnosis holds great promise in red...

Extended Linear Confined Zipper Cascaded Reaction for Highly Efficient Intracellular Imaging and Assisting Diagnosis of Thyroid Cancer.

Highly sensitive detection and in situ tracing analysis of small-molecule biomarkers are particularl...

An Ultrasound Image-Based Deep Learning Radiomics Nomogram for Differentiating Between Benign and Malignant Indeterminate Cytology (Bethesda III) Thyroid Nodules: A Retrospective Study.

RATIONALE AND OBJECTIVES: Our objective is to develop and validate a deep learning radiomics nomogra...

Proteomic analysis reveals modulation of key proteins in follicular thyroid cancer progression.

BACKGROUND: Cytopathology cannot be used to reliably distinguish follicular thyroid adenoma (FTA) fr...

Artificial intelligence-assisted CT radiomics: redefining preoperative prediction of lateral cervical lymph node metastasis in papillary thyroid carcinoma.