Thyroid

A deep-learning model to assist thyroid nodule diagnosis and management - Authors' reply.

A deep-learning model to assist thyroid nodule diagnosis and management.

Comparison of British Thyroid Association, American College of Radiology TIRADS and Artificial Intelligence TIRADS with histological correlation: diagnostic performance for predicting thyroid malignancy and unnecessary fine needle aspiration rate.

OBJECTIVES: To compare diagnostic performance of British Thyroid Association (BTA), American College...

Recognition of Thyroid Ultrasound Standard Plane Images Based on Residual Network.

Ultrasound is one of the critical methods for diagnosis and treatment in thyroid examination. In cli...

Joint Detection of Tap and CEA Based on Deep Learning Medical Image Segmentation: Risk Prediction of Thyroid Cancer.

In recent years, the incidence of thyroid nodules has shown an increasing trend year by year and has...

Role of Regulatory Non-Coding RNAs in Aggressive Thyroid Cancer: Prospective Applications of Neural Network Analysis.

Thyroid cancer (TC) is the most common endocrine malignancy. Most TCs have a favorable prognosis, wh...

Prevention of non-recurrent laryngeal nerve injury in robotic thyroidectomy: imaging and technique.

INTRODUCTION: The aim of this report was to summarize observations, evaluate the feasibility, provid...

Machine learning for the prediction of bone metastasis in patients with newly diagnosed thyroid cancer.

OBJECTIVES: This study aimed to establish a machine learning prediction model that can be used to pr...

Adequacy and Effectiveness of Watson For Oncology in the Treatment of Thyroid Carcinoma.

BACKGROUND: IBM's Watson for Oncology (WFO) is an artificial intelligence tool that trains by acquir...

Machine learning-based prediction model using clinico-pathologic factors for papillary thyroid carcinoma recurrence.

This study analyzed the prognostic significance of clinico-pathologic factors, including the number ...

Thyroid gland delineation in noncontrast-enhanced CTs using deep convolutional neural networks.

The purpose of this study is to develop a deep learning method for thyroid delineation with high acc...

Discrimination of malignant from benign thyroid lesions through neural networks using FTIR signals obtained from tissues.

The current gold standard in cancer diagnosis-the microscopic examination of hematoxylin and eosin (...

On the identification of thyroid nodules using semi-supervised deep learning.

Detecting malign cases from thyroid nodule examinations is crucial in healthcare particularly to imp...

Transoral endoscopic thyroidectomy vestibular approach (TOETVA): Our outcomes from Turkey.

OBJECTIVES: The Transoral Endoscopic Thyroidectomy Vestibular Approach (TOETVA) was described in 201...

Clinical Case Report: Dissociation of Clinical Course of Coexisting Autoimmune Hepatitis and Graves Disease.

OBJECTIVE: Concurrent autoimmune disorders, including autoimmune hepatitis (AIH), with Graves diseas...

Hashimoto Encephalopathy in Pediatrics: Report of 3 Cases.

OBJECTIVE: To describe the rare occurrence of pediatric Hashimoto encephalopathy in 3 patients.

Segmentation and classification of thyroid follicular neoplasm using cascaded convolutional neural network.

In this paper, we present a segmentation and classification method for thyroid follicular neoplasms ...

Artificial Intelligence in Thyroid Fine Needle Aspiration Biopsies.

BACKGROUND: From cell phones to aerospace, artificial intelligence (AI) has wide-reaching influence ...

Prognostic Value of Serum Thyroglobulin Measured at 48 Hours Versus 72 Hours after Second Dose of Recombinant Human Thyrotropin in Surveillance of Well-Differentiated Thyroid Cancer.

OBJECTIVE: The sensitivity of thyroglobulin (Tg) to detect differentiated thyroid cancer recurrence ...

Ensemble machine learning for the prediction of patient-level outcomes following thyroidectomy.

BACKGROUND: Accurate prediction of thyroidectomy complications is necessary to inform treatment deci...

Artificial intelligence to predict the BRAFV600E mutation in patients with thyroid cancer.

PURPOSE: To investigate whether a computer-aided diagnosis (CAD) program developed using the deep le...