Thyroid

Proteogenomic characterization delineates clinically relevant subtypes of advanced differentiated thyroid cancer.

Advanced differentiated thyroid cancer (DTC) is characterized by limited therapeutic options and unf...

Artificial intelligence-enabled ultrasound diagnosis and stratification of follicular thyroid neoplasms: a multi-center study.

Preoperatively distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FT...

Inflammatory protein expression patterns in Hashimoto's thyroiditis: a cross-sectional observational study.

Adverse reactions of PD-1/PD-L1 inhibitors in cancer: FAERS database analysis and protocols to mitigate immune-related events in elderly patients and when using pembrolizumab and atezolizumab.

OBJECTIVE: This study aimed to characterize adverse drug reactions (ADRs) associated with programmed...

Feasibility of an Augmented Reality Artificial Intelligence Tool for Real-Time Assessment of Thyroid Fine-Needle Aspiration Adequacy.

PURPOSE: To evaluate the feasibility of developing an artificial intelligence application for real-t...

Identification of the immune-related diagnostic biomarkers between Graves' disease and thyroid carcinoma based on comprehensive bioinformatics analysis and machine learning.

Increasing evidence suggests that Graves' disease (GD) may increase the risk of thyroid cancer (THCA...

Integrative multi-omics refines the molecular subtypes of thyroid cancers and enhances cancer-progression prediction: a retrospective cohort study.

BACKGROUND: Current molecular classification model for thyroid cancer (TC), which relies on BRAF-RAS...

A transformer and 3D CNN-based feature fusion network with interpretable ability for Raman spectra analysis: improving the diagnosis of thyroid cancer.

Accurate differentiation of benign and malignant thyroid lesions continues to pose a significant cli...

Multimodal ultrasound and artificial intelligence for characterization of thyroid nodules in Hashimoto's thyroiditis: current challenges and future perspectives.

Patients with Hashimoto's thyroiditis (HT) frequently present with concurrent nodular lesions such a...

Machine Learning Prediction of Recurrence in Pediatric Thyroid Cancer: Malignant Endocrine Tumors Cohort Analysis Using XGBoost and SHAP.

CONTEXT: Pediatric differentiated thyroid carcinoma (DTC) often presents with advanced disease but g...

Discovery of potent ALK tyrosine kinase inhibitors for thyroid cancer via machine learning modeling, molecular docking, MD simulations, and DFT study.

The ever-increasing need for effective therapeutic management of thyroid cancer (TC) necessitates th...

R-GAT: cancer document classification leveraging graph-based residual network for scenarios with limited data.

Accurate classification of cancer-related biomedical abstracts is critical for advancing cancer info...

Comparable survival after lobectomy and total thyroidectomy for T3b differentiated thyroid carcinoma: A population-based study.

BACKGROUND: The 2025 American Thyroid Association guidelines recommend total thyroidectomy for all T...

A novel automated parathyroid glands detection and segmentation method in thyroidectomy.

BACKGROUND: Intraoperative preservation of parathyroid glands (PGs) remained a significant challenge...

Training the diagnostic artificial intelligence in thyroid sonography: how well is deep learning truly learning?

INTRODUCTION: The use of artificial intelligence (AI) for TI-RADS classification in neck sonography ...

Multidisciplinary Team Diagnosis and Treatment of well-differentiated thyroid carcinoma: Current Landscape and Future Prospects.

BACKGROUND: The incidence of thyroid cancer has increased markedly in recent years, largely driven b...

Interpretable Machine Learning Model Using Digitized US Features for Classifying Complex Thyroid Nodules.

Purpose To develop a digitized integrated feature-based interpretable machine learning classificatio...

Improving Diagnostic Precision in Thyroid Pathology by Synergistic Use of AI and Molecular Markers.

OBJECTIVES: For indeterminate thyroid nodules, molecular tests offer high negative predictive value ...

Machine learning-based classification of papillary thyroid carcinoma versus multinodular goiter using preoperative laboratory and cytology data.

A Deep Learning Framework for Predicting Teprotumumab Treatment Response in Thyroid Eye Disease.

PURPOSE: To develop and evaluate a deep learning-based framework for quantifying thyroid eye disease...

ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning.

Co-fractionation mass spectrometry (CF-MS) enables large-scale profiling of endogenous protein-prote...