Thyroid

Ultrasound Image-Based Diagnosis of Malignant Thyroid Nodule Using Artificial Intelligence.

Computer-aided diagnosis systems have been developed to assist doctors in diagnosing thyroid nodules to reduce errors made by traditional diagnosis methods, which are mainly based on the experiences of doctors. Therefore, the performance of such systems plays an important role in enhancing the quality of a diagnosing task. Although there have been the state-of-the art studies regarding this proble...

AIBx, Artificial Intelligence Model to Risk Stratify Thyroid Nodules.

Current classification systems for thyroid nodules are very subjective. Artificial intelligence (AI) algorithms have been used to decrease subjectivity in medical image interpretation. One out of 2 women over the age of 50 years may have a thyroid nodule and at present the only way to exclude malignancy is through invasive procedures for those that are suspicious on ultrasonography. Hence, there ...

Robotic Transaxillary Hemithyroidectomy Using the da Vinci SP Robotic System: Initial Experience With 10 Consecutive Cases.

Many studies have shown the operative feasibility and safety of robotic thyroidectomy. However, there is still a concern on the operative invasivenes...

Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.

BACKGROUND: Relatives of patients with bladder cancer have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after cor...

Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training.

PURPOSE: This study aimed to validate a deep learning model's diagnostic performance in using computed tomography (CT) to diagnose cervical lymph node...

Automatic diagnosis for thyroid nodules in ultrasound images by deep neural networks.

Thyroid cancer is a disease in which the first symptom is a nodule in the thyroid region of the neck. It is one of the cancers with the highest incide...

Application of a machine learning algorithm to predict malignancy in thyroid cytopathology.

BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) comprises 6 categories used for the diagnosis of thyroid fine-needle aspi...

New Insights and Methods in the Approach to Thalassemia Major: The Lesson From the Case of Adrenal Insufficiency.

Thalassemia Major (TM) is a complex pathology that needs a highly skilled approach. Endocrine comorbidities are nowadays the most important complicat...

Nodular Thyroid Disease in the Era of Precision Medicine.

Management of thyroid nodules in the era of precision medicine is continuously changing. Neck ultrasound plays a pivotal role in the diagnosis and sev...

Convolutional Neural Network for Breast and Thyroid Nodules Diagnosis in Ultrasound Imaging.

OBJECTIVE: The incidence of superficial organ diseases has increased rapidly in recent years. New methods such as computer-aided diagnosis (CAD) are w...

Differentiation of thyroid nodules on US using features learned and extracted from various convolutional neural networks.

Thyroid nodules are a common clinical problem. Ultrasonography (US) is the main tool used to sensitively diagnose thyroid cancer. Although US is non-i...

Diagnosis of Parathyroid Adenomas with New Ultrasound Imaging Modalities.

Ultrasound technology is becoming an integral part of diagnosing parathyroid adenomas. Careful ultrasound evaluation with b-mode, shear wave elastogra...

Automatic cancer tissue detection using multispectral photoacoustic imaging.

PURPOSE: In the case of multispecimen study to locate cancer regions, such as in thyroidectomy and prostatectomy, a significant labor-intensive proces...

NEOADJUVANT LENVATINIB IN ADVANCED UNRESECTABLE MEDULLARY THYROID CARCINOMA: A CASE REPORT.

OBJECTIVE: Medullary thyroid carcinoma, a rare form of thyroid cancer, is typically managed with surgical excision. However, in patients with locally-...

Machine Learning Prediction of Radiofrequency Thermal Ablation Efficacy: A New Option to Optimize Thyroid Nodule Selection.

BACKGROUND: Radiofrequency (RF) is a therapeutic modality for reducing the volume of large benign thyroid nodules. If thermal therapies are interprete...

Computer-Aided Diagnosis Systems in Diagnosing Malignant Thyroid Nodules on Ultrasonography: A Systematic Review and Meta-Analysis.

BACKGROUND: Computer-aided diagnosis (CAD) systems are being applied to the ultrasonographic diagnosis of malignant thyroid nodules, but it remains co...

Diagnosis of Thyroid Nodules: Performance of a Deep Learning Convolutional Neural Network Model vs. Radiologists.

Computer-aided diagnosis (CAD) systems hold potential to improve the diagnostic accuracy of thyroid ultrasound (US). We aimed to develop a deep learni...

Machine learning-based multiparametric MRI radiomics for predicting the aggressiveness of papillary thyroid carcinoma.

PURPOSE: To investigate the predictive capability of machine learning-based multiparametric magnetic resonance (MR) imaging radiomics for evaluating t...

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction.

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyro...

Safety and efficacy of transoral robotic and endoscopic thyroidectomy: The first 100 cases.

BACKGROUND: The aim of this study was to evaluate the safety and efficacy of transoral robotic and endoscopic thyroidectomy.