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Thyroid Neoplasms

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A comparison between deep learning convolutional neural networks and radiologists in the differentiation of benign and malignant thyroid nodules on CT images.

Endokrynologia Polska
INTRODUCTION: We designed 5 convolutional neural network (CNN) models and ensemble models to differentiate malignant and benign thyroid nodules on CT, and compared the diagnostic performance of CNN models with that of radiologists.

Thyroid gland delineation in noncontrast-enhanced CTs using deep convolutional neural networks.

Physics in medicine and biology
The purpose of this study is to develop a deep learning method for thyroid delineation with high accuracy, efficiency, and robustness in noncontrast-enhanced head and neck CTs. The cross-sectional analysis consisted of six tests, including randomized...

Discrimination of malignant from benign thyroid lesions through neural networks using FTIR signals obtained from tissues.

Analytical and bioanalytical chemistry
The current gold standard in cancer diagnosis-the microscopic examination of hematoxylin and eosin (H&E)-stained biopsies-is prone to bias since it greatly relies on visual examination. Hence, there is a need to develop a more sensitive and specific ...

Antibody Supervised Training of a Deep Learning Based Algorithm for Leukocyte Segmentation in Papillary Thyroid Carcinoma.

IEEE journal of biomedical and health informatics
The quantity of leukocytes in papillary thyroid carcinoma (PTC) potentially have prognostic and treatment predictive value. Here, we propose a novel method for training a convolutional neural network (CNN) algorithm for segmenting leukocytes in PTCs....

Segmentation and classification of thyroid follicular neoplasm using cascaded convolutional neural network.

Physics in medicine and biology
In this paper, we present a segmentation and classification method for thyroid follicular neoplasms based on a combination of the prior-based level set method and deep convolutional neural network. The proposed method aims to discriminate thyroid fol...

Artificial Intelligence in Thyroid Fine Needle Aspiration Biopsies.

Acta cytologica
BACKGROUND: From cell phones to aerospace, artificial intelligence (AI) has wide-reaching influence in the modern age. In this review, we discuss the application of AI solutions to an equally ubiquitous problem in cytopathology - thyroid fine needle ...

Prognostic Value of Serum Thyroglobulin Measured at 48 Hours Versus 72 Hours after Second Dose of Recombinant Human Thyrotropin in Surveillance of Well-Differentiated Thyroid Cancer.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVE: The sensitivity of thyroglobulin (Tg) to detect differentiated thyroid cancer recurrence increases with the rise of the thyrotropin level. Since 1998, recombinant human thyrotropin (rhTSH) has been commercially available for this purpose. ...

Artificial intelligence to predict the BRAFV600E mutation in patients with thyroid cancer.

PloS one
PURPOSE: To investigate whether a computer-aided diagnosis (CAD) program developed using the deep learning convolutional neural network (CNN) on neck US images can predict the BRAFV600E mutation in thyroid cancer.

Diagnosis of thyroid neoplasm using support vector machine algorithms based on platelet RNA-seq.

Endocrine
OBJECTIVE: To assess the capacity of support vector machine (SVM) algorithms that are developed based on platelet RNA-seq data in identifying thyroid neoplasm patients and differentiating patients with thyroid adenomas, papillary thyroid cancer and m...