Thyroid

Serum PD-1 regulation and PD-1 expression of CD4+Foxp3+ regulatory T cells in patients in thyroid eye disease associated with immunosuppression treatment.

PURPOSE: Thyroid eye disease (TED) primarily occurs in hyperthyroid patients, sometimes resulting in poor visual prognosis. Although other autoimmune diseases have been reported to be associated with serum programmed cell death 1 (PD-1), the relationship with TED remains unknown. This study investigated the relationship between TED and immune checkpoint molecules.

Identification and verification of the optimal feature genes of ferroptosis in thyroid-associated orbitopathy.

BACKGROUND: Thyroid-associated orbitopathy (TAO) is an autoimmune inflammatory disorder of the orbital adipose tissue, primarily causing oxidative stress injury and tissue remodeling in the orbital connective tissue. Ferroptosis is a form of programmed cell death driven by the accumulation of reactive oxygen species (ROS), iron metabolism disorder, and lipid peroxidation. This study aims to identi...

Linsitinib inhibits proliferation and induces apoptosis of both IGF-1R and TSH-R expressing cells.

BACKGROUND: The insulin-like growth factor 1 receptor (IGF-1R) and the thyrotropin receptor (TSH-R) are expressed on orbital cells and thyrocytes. The...

Enhancing Thyroid Pathology With Artificial Intelligence: Automated Data Extraction From Electronic Health Reports Using RUBY.

PURPOSE: Thyroid nodules are common in the general population, and assessing their malignancy risk is the initial step in care. Surgical exploration r...

Subclinical/overt hypothyroidism may be associated with diminished ovarian reserve in infertile women independent of thyroid autoimmunity.

OBJECTIVE: To investigate the association between thyroid dysfunction or thyroid autoimmunity (TAI) and diminished ovarian reserve (DOR).

Effective analysis of thyroid toxicity and mechanisms of acetyltributyl citrate using network toxicology, molecular docking, and machine learning strategies.

The growing prevalence of environmental pollutants has raised concerns about their potential role in thyroid dysfunction and related disorders. Previo...

Multiple instance learning method based on convolutional neural network and self-attention for early cancer detection.

Early cancer detection using T-cell receptor sequencing (TCR-seq) and multiple instances learning methods has shown significant effectiveness. We intr...

Potential impact of organophosphate esters on thyroid eye disease based on machine learning and molecular docking.

Organophosphate esters (OPEs) are widely used as flame retardants and plasticizers in daily commodities and building materials. Some OPEs, acting as a...

Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models.

Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hyperthyroidism or hypothyroidism, which can significa...

Multiple-Instance Learning for thyroid gland disease classification: A hands-on experience.

The morphological diagnosis of thyroid gland neoplasms presents a dual challenge: it requires the expertise of highly trained specialists and consider...

The added value of including thyroid nodule features into large language models for automatic ACR TI-RADS classification based on ultrasound reports.

OBJECTIVE: The ACR Thyroid Imaging, Reporting, and Data System (TI-RADS) uses a score based on ultrasound (US) imaging to stratify the risk of nodule ...

An ultrasonography of thyroid nodules dataset with pathological diagnosis annotation for deep learning.

Ultrasonography (US) of thyroid nodules is often time consuming and may be inconsistent between observers, with a low positivity rate for malignancy i...

TIRADS-based artificial intelligence systems for ultrasound images of thyroid nodules: protocol for a systematic review.

PURPOSE: The thyroid imaging reporting and data system (TIRADS) was developed as a standard global term to describe thyroid nodule risk features, aimi...

Development and Validation of a Prediction Model for Co-Occurring Moderate-to-Severe Anxiety Symptoms in First-Episode and Drug Naïve Patients With Major Depressive Disorder.

Moderate-to-severe anxiety symptoms are severe and common in patients with major depressive disorder (MDD) and have a significant impact on MDD patie...

Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.

OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicular thyroid carcinoma (FTC) and follicular thyroid a...

Deep learning based analysis of dynamic video ultrasonography for predicting cervical lymph node metastasis in papillary thyroid carcinoma.

BACKGROUND: Cervical lymph node metastasis (CLNM) is the most common form of thyroid cancer metastasis. Accurate preoperative CLNM diagnosis is of mor...

The study on ultrasound image classification using a dual-branch model based on Resnet50 guided by U-net segmentation results.

In recent years, the incidence of nodular thyroid diseases has been increasing annually. Ultrasonography has become a routine diagnostic tool for thyr...

Artificial intelligence-enhanced infrared thermography as a diagnostic tool for thyroid malignancy detection.

INTRODUCTION: Thyroid nodules are common, and investigation is crucial for excluding malignancy. Increased intranodular vascularity is frequently obse...

Neural network-based automated proptosis measurement using computed tomography images for patients with thyroid-associated orbitopathy.

The purpose of this study was to evaluate the clinical feasibility and reliability of a neural network (NN)-based automated proptosis measurement syst...

Classifying driver mutations of papillary thyroid carcinoma on whole slide image: an automated workflow applying deep convolutional neural network.

BACKGROUND: Informative biomarkers play a vital role in guiding clinical decisions regarding management of cancers. We have previously demonstrated th...