Thyroid

Visualization of Organ Movements Using Automatic Region Segmentation of Swallowing CT

This study presents the first report on the development of an artificial intelligence (AI) for aut...

AI in Oncology: Transforming Cancer Detection through Machine Learning and Deep Learning Applications

Artificial intelligence (AI) has potential to revolutionize the field of oncology by enhancing the...

[Two cases of transaxillary thyroidectomy assisted by a domestic single-port robotic system].

Exploiting pair correlation function to describe biological tissue structure

Multiplexed imaging technologies now enable the simultaneous profiling of hundreds to thousands of m...

Significant Reduction in Manual Annotation Costs in Ultrasound Medical Image Database Construction Through Step by Step Artificial Intelligence Pre-annotation

This study investigates the feasibility of reducing manual image annotation costs in medical image d...

Enhancing Diagnostic Precision in Thyroid Nodule Classification: A Deep Learning Approach to Automated Ultrasound Image Analysis

Escalating thyroid nodule prevalence necessitates precise ultrasonographic diagnosis, which is const...

Machine learning-Based Classification of Papillary Thyroid Carcinoma Versus Multinodular Goiter Using Preoperative Laboratory and Cytology Data

Thyroid nodules are frequently encountered in clinical practice, with their detection increasing due...

A nomogram for predicting the nature of thyroid adenomatoid nodules on ultrasound: a dual-center study.

PURPOSE: Thyroid Imaging Reporting and Data System (TIRADS) does not perform well in thyroid adenoma...

Interpretable AI-driven multi-objective risk prediction in heart failure patients with thyroid dysfunction.

INTRODUCTION: Heart Failure (HF) complicated by thyroid dysfunction presents a complex clinical chal...

The diagnostic value of convolutional neural networks in thyroid cancer detection using ultrasound images.

OBJECTIVE: To extract and analyze the image features of two-dimensional ultrasound images and elasti...

Intelligent diagnosis of thyroid nodules with AI ultrasound assistance and cytology classification.

OBJECTIVE: Accurate evaluation of thyroid nodules is crucial for effective management; however, meth...

CLIP-TNseg: A Multi-Modal Hybrid Framework for Thyroid Nodule Segmentation in Ultrasound Images

Thyroid nodule segmentation in ultrasound images is crucial for accurate diagnosis and treatment p...

Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Papillary Thyroid Carcinoma Variants.

BACKGROUND: Hürthle cell (HCC) and columnar cell variants (CCV) are rare subtypes of thyroid cancer.

Reducing Overtreatment of Indeterminate Thyroid Nodules Using a Multimodal Deep Learning Model

Objective: Molecular testing (MT) classifies cytologically indeterminate thyroid nodules as benign...

Predicting excellent response to radioiodine in differentiated thyroid cancer using machine learning.

OBJECTIVE: If excellent response (ER) occurs after radioactive iodine (RAI) treatment in patients wi...

BertTCR: a Bert-based deep learning framework for predicting cancer-related immune status based on T cell receptor repertoire.

The T cell receptor (TCR) repertoire is pivotal to the human immune system, and understanding its nu...

[Preoperative Evaluation of Cervical Lymph Node Metastasis in Patients With Hashimoto's Thyroiditis Combined With Thyroid Papillary Carcinoma Using Machine Learning and Radiomics-Based Features: A Preliminary Study].

OBJECTIVE: To analyze the radiomic and clinical features extracted from 2D ultrasound images of thyr...

From Bench-to-Bedside: How Artificial Intelligence is Changing Thyroid Nodule Diagnostics, a Systematic Review.

CONTEXT: Use of artificial intelligence (AI) to predict clinical outcomes in thyroid nodule diagnost...

Improved Diagnostic Accuracy of Thyroid Fine-Needle Aspiration Cytology with Artificial Intelligence Technology.

Artificial intelligence (AI) is increasingly being applied in pathology and cytology, showing promi...

A novel deep machine learning algorithm with dimensionality and size reduction approaches for feature elimination: thyroid cancer diagnoses with randomly missing data.

Thyroid cancer incidences endure to increase even though a large number of inspection tools have bee...

Deep-Learning Based Automated Segmentation and Quantitative Volumetric Analysis of Orbital Muscle and Fat for Diagnosis of Thyroid Eye Disease.

PURPOSE: Thyroid eye disease (TED) is characterized by proliferation of orbital tissues and complica...