AI Medical Compendium Topic

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Thyroid Nodule

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Automatic detection of thyroid nodules with a real-time artificial intelligence system in a real clinical scenario and the associated influencing factors.

Clinical hemorheology and microcirculation
BACKGROUND: At present, most articles mainly focused on the diagnosis of thyroid nodules by using artificial intelligence (AI), and there was little research on the detection performance of AI in thyroid nodules.

The Application of Artificial Intelligence in Thyroid Nodules: A Systematic Review Based on Bibliometric Analysis.

Endocrine, metabolic & immune disorders drug targets
BACKGROUND: Thyroid nodules are common lesions in benign and malignant thyroid diseases. More and more studies have been conducted on the feasibility of artificial intelligence (AI) in the detection, diagnosis, and evaluation of thyroid nodules. The ...

ChatGPT-assisted deep learning model for thyroid nodule analysis: beyond artifical intelligence.

Medical ultrasonography
AIMS: To develop a deep learning model, with the aid of ChatGPT, for thyroid nodules, utilizing ultrasound images. The cytopathology of the fine needle aspiration biopsy (FNAB) serves as the baseline.

Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study.

The Lancet. Digital health
BACKGROUND: Strategies for integrating artificial intelligence (AI) into thyroid nodule management require additional development and testing. We developed a deep-learning AI model (ThyNet) to differentiate between malignant tumours and benign thyroi...

Use of artificial intelligence and machine learning for estimating malignancy risk of thyroid nodules.

Current opinion in endocrinology, diabetes, and obesity
PURPOSE OF REVIEW: Current methods for thyroid nodule risk stratification are subjective, and artificial intelligence algorithms have been used to overcome this shortcoming. In this review, we summarize recent developments in the application of artif...

Ultrasonographic Thyroid Nodule Classification Using a Deep Convolutional Neural Network with Surgical Pathology.

Journal of digital imaging
Ultrasonography with fine-needle aspiration biopsy is commonly used to detect thyroid cancer. However, thyroid ultrasonography is prone to subjective interpretations and interobserver variabilities. The objective of this study was to develop a thyroi...

Nodule Localization in Thyroid Ultrasound Images with a Joint-Training Convolutional Neural Network.

Journal of digital imaging
The accurate localization of nodules in ultrasound images can convey crucial information to support a reliable diagnosis. However, this is usually challenging due to low contrast and image artifacts, especially in thyroid ultrasound images where nodu...

Thyroid Nodule Malignancy Risk Stratification Using a Convolutional Neural Network.

Ultrasound quarterly
This study evaluates the performance of convolutional neural networks (CNNs) in risk stratifying the malignant potential of thyroid nodules alongside traditional methods such as American College of Radiology Thyroid Imaging Reporting and Data System ...

Recognition of calcifications in thyroid nodules based on attention-gated collaborative supervision network of ultrasound images.

Journal of X-ray science and technology
BACKGROUND: Calcification is an important criterion for classification between benign and malignant thyroid nodules. Deep learning provides an important means for automatic calcification recognition, but it is tedious to annotate pixel-level labels f...