INTRODUCTION: The detection rate of benign thyroid nodules is increasing every year, with some affected patients experiencing symptoms. Ultrasound-guided thermal ablation can reduce the volume of nodules to alleviate symptoms. As the degree and speed...
The funding details have been incorporated upon author's request in the funding section of this articles entitled "Superresolution based Nodule Localization in Thyroid Ultrasound Images through Deep Learning," 2024, 20, e15734056269264 [1]. The origi...
Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
39127110
OBJECTIVES: To evaluate the efficacy of combining predictive artificial intelligence (AI) and image similarity model to risk stratify thyroid nodules, using retrospective external validation study.
OBJECTIVE: Approximately 30 % of thyroid nodules yield an indeterminate diagnosis through conventional diagnostic strategies. The aim of this study was to develop machine learning (ML) models capable of identifying papillary thyroid carcinomas using ...
PURPOSE: This study aims to assess the diagnostic efficacy of Korean Thyroid imaging reporting and data system (K-TIRADS), S-Detect software and contrast-enhanced ultrasound (CEUS) when employed individually, as well as their combined application, fo...
AIMS: This study aims to use deep learning (DL) to classify thyroid nodules as benign and malignant with ultrasonography (US). In addition, this study investigates the impact of DL on the diagnostic success of radiologists with different experiences....
INTRODUCTION: Thyroid nodules are common, and investigation is crucial for excluding malignancy. Increased intranodular vascularity is frequently observed in malignant tumors, which can be detected through increased skin surface temperatures using no...
Thyroid : official journal of the American Thyroid Association
39405186
Thyroid nodules are challenging to accurately characterize on ultrasound (US), though the emergence of risk stratification systems and more recently artificial intelligence (AI) algorithms has improved nodule classification. The purpose of this stud...
BACKGROUND: Multiple artificial intelligence (AI) systems have been approved to risk-stratify thyroid nodules through sonographic characterization. We sought to validate the ability of one such AI system, Koios DS (Koios Medical, Chicago, IL), to aid...
PURPOSE: Thyroid nodules are highly prevalent in the general population, posing a clinical challenge in accurately distinguishing between benign and malignant cases. This study aimed to investigate the diagnostic performance of different strategies, ...