AIMC Topic: Thyroid Gland
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Multiple-Instance Learning for thyroid gland disease classification: A hands-on experience.
Computers in biology and medicine
Nov 28, 2024
The morphological diagnosis of thyroid gland neoplasms presents a dual challenge: it requires the expertise of highly trained specialists and considerable time, particularly when evaluating multiple whole slide images (WSIs) from a single patient. Th...
The added value of including thyroid nodule features into large language models for automatic ACR TI-RADS classification based on ultrasound reports.
Japanese journal of radiology
Nov 25, 2024
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 malignancy and recommend appropriate follow-up. This study aims to analyze US reports and explore ho...
An ultrasonography of thyroid nodules dataset with pathological diagnosis annotation for deep learning.
Scientific data
Nov 23, 2024
Ultrasonography (US) of thyroid nodules is often time consuming and may be inconsistent between observers, with a low positivity rate for malignancy in biopsies. Even after determining the ultrasound Thyroid Imaging Reporting and Data System (TIRADS)...
TIRADS-based artificial intelligence systems for ultrasound images of thyroid nodules: protocol for a systematic review.
Journal of ultrasound
Nov 20, 2024
PURPOSE: The thyroid imaging reporting and data system (TIRADS) was developed as a standard global term to describe thyroid nodule risk features, aiming to address issues such as variability and low reproducibility in nodule feature detection and int...
Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Nov 18, 2024
OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) and construct a tool for preoperative noninvasive predicting FTC and FTA.
The study on ultrasound image classification using a dual-branch model based on Resnet50 guided by U-net segmentation results.
BMC medical imaging
Nov 18, 2024
In recent years, the incidence of nodular thyroid diseases has been increasing annually. Ultrasonography has become a routine diagnostic tool for thyroid nodules due to its high real-time capabilities and low invasiveness. However, thyroid images obt...
Artificial intelligence-enhanced infrared thermography as a diagnostic tool for thyroid malignancy detection.
Annals of medicine
Nov 8, 2024
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...
A novel meta learning based stacked approach for diagnosis of thyroid syndrome.
PloS one
Nov 1, 2024
Thyroid syndrome, a complex endocrine disorder, involves the dysregulation of the thyroid gland, impacting vital physiological functions. Common causes include autoimmune disorders, iodine deficiency, and genetic predispositions. The effects of thyro...
Assessment of the Diagnostic Performance of a Commercially Available Artificial Intelligence Algorithm for Risk Stratification of Thyroid Nodules on Ultrasound.
Thyroid : official journal of the American Thyroid Association
Oct 15, 2024
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...
Improving the diagnostic strategy for thyroid nodules: a combination of artificial intelligence-based computer-aided diagnosis system and shear wave elastography.
Endocrine
Oct 7, 2024
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, ...
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