AIMC Topic: Thyroid Gland

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Thyroid Function Effects of Mixed Exposure to Urinary Trihalomethanes and Haloacetic Acids: Based on an Integrated Framework of Exposure Assessment, Qualitative Association, and Quantitative Attribution.

Environmental science & technology
Toxicological studies have demonstrated that disinfection byproducts (DBPs) can disrupt thyroid function; however, human epidemiological evidence remains limited. The existing studies focus on a limited number of compounds and lack detailed investiga...

Enhancing automatic diagnosis of thyroid nodules from ultrasound scans leveraging deep learning models.

Scientific reports
The thyroid gland is prone to various diseases, including thyroid nodules. Ultrasound is the primary diagnostic tool, but classification accuracy is often limited by radiologist expertise. Integrating Artificial Intelligence, particularly Deep Learni...

AI-assisted recurrent laryngeal nerve identification during endoscopic/robotic thyroid surgery based on the CMC-UNet model: a multicenter retrospective study.

Journal of robotic surgery
During endoscopic or robotic-assisted thyroid surgery, the field of view may be restricted by tissue swelling or bleeding. These Limitations make delicate surgical manipulation in the confined space more challenging. This study proposes an artificial...

A comparative analysis of deep learning architectures for thyroid tissue classification with hyperspectral imaging.

Scientific reports
Hyperspectral imaging has shown significant applicability in the medical field, particularly for its ability to represent spectral information that can differentiate specific biomolecular characteristics in tissue samples. However, the complexity of ...

Improved bio-inspired with machine learning computing approach for thyroid prediction.

Scientific reports
Thyroid illness is widely recognised as a prevalent health condition that can result in a range of health disorders. Thyroid illnesses, namely hypothyroidism and hyperthyroidism, are widespread worldwide and present considerable health consequences. ...

Ultrasound-based classification of follicular thyroid Cancer using deep convolutional neural networks with transfer learning.

Scientific reports
This study aimed to develop and validate convolutional neural network (CNN) models for distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA). Additionally, this current study compared the performance of CNN models wi...

Enhancing weakly supervised data augmentation networks for thyroid nodule assessment using traditional and doppler ultrasound images.

Computers in biology and medicine
Thyroid ultrasound (US) is an essential tool for detecting and characterizing thyroid nodules. In this study, we propose an innovative approach to enhance thyroid nodule assessment by integrating Doppler US images with grayscale US images through wea...

Impact of Field-of-view Zooming and Segmentation Batches on Radiomics Features Reproducibility and Machine Learning Performance in Thyroid Scintigraphy.

Clinical nuclear medicine
BACKGROUND: Thyroid diseases are the second most common hormonal disorders, necessitating accurate diagnostics. Advances in artificial intelligence and radiomics have enhanced diagnostic precision by analyzing quantitative imaging features. However, ...

Preliminary analysis of AI-based thyroid nodule evaluation in a non-subspecialist endocrinology setting.

Endocrine
PURPOSE: Thyroid nodules are commonly evaluated using ultrasound-based risk stratification systems, which rely on subjective descriptors. Artificial intelligence (AI) may improve assessment, but its effectiveness in non-subspecialist settings is uncl...