Thyroid

Automatic differentiation of thyroid scintigram by deep convolutional neural network: a dual center study.

BACKGROUND: Tc-pertechnetate thyroid scintigraphy is a valid complementary avenue for evaluating thyroid disease in the clinic, the image feature of thyroid scintigram is relatively simple but the interpretation still has a moderate consistency among physicians. Thus, we aimed to develop an artificial intelligence (AI) system to automatically classify the four patterns of thyroid scintigram.

Positive effects of thyroid replacement therapy on assisted reproductive technology outcomes in women with subclinical hypothyroidism with positive thyroid peroxidase autoantibodies.

OBJECTIVE: To study the beneficial effects of thyroid replacement therapy (TRT) on pregnancy outcomes in patients with subclinical hypothyroidism (SCl hypoT) with respect to thyroid peroxidase (TPO) autoantibodies.

Thyroglobulin Levels in Patients who have Undergone Hemithyroidectomy for Differentiated Thyroid Cancer. An Assessment of Levels and Trends at a Tertiary Referral Centre.

Subramanian Kannan Serum thyroglobulin (Tg) and thyroglobulin antibody (TgAb) levels are used to monitor patients with differentiated thyroid cancer (...

A deep learning-based method for detecting and classifying the ultrasound images of suspicious thyroid nodules.

PURPOSE: The incidence of thyroid cancer has significantly increased in the last few decades. However, diagnosis of the thyroid nodules is labor and t...

Prognostic biomarkers for predicting papillary thyroid carcinoma patients at high risk using nine genes of apoptotic pathway.

Aberrant expressions of apoptotic genes have been associated with papillary thyroid carcinoma (PTC) in the past, however, their prognostic role and ut...

Machine intelligence in non-invasive endocrine cancer diagnostics.

Artificial intelligence (AI) has illuminated a clear path towards an evolving health-care system replete with enhanced precision and computing capabil...

Single-port transaxillary robotic thyroidectomy (START): 200-cases with two-step retraction method.

BACKGROUND: This study aims to report the results of a pioneering clinical study using the single-port transaxillary robotic thyroidectomy (START) for...

Quantifying the Impacts of Pre- and Post-Conception TSH Levels on Birth Outcomes: An Examination of Different Machine Learning Models.

BACKGROUND: While previous studies identified risk factors for diverse pregnancy outcomes, traditional statistical methods had limited ability to quan...

Artificial Intelligence in Toxicological Pathology: Quantitative Evaluation of Compound-Induced Follicular Cell Hypertrophy in Rat Thyroid Gland Using Deep Learning Models.

Digital pathology has recently been more broadly deployed, fueling artificial intelligence (AI) application development and more systematic use of ima...

Graves Disease Following Subacute Thyroiditis in a Chinese Man.

BACKGROUND/OBJECTIVE: The development of Graves disease (GD) after subacute thyroiditis (SAT) is rare, with approximately 31 reported cases, of which ...

Comparison of Perioperative Outcomes Using the da Vinci S, Si, X, and Xi Robotic Platforms for BABA Robotic Thyroidectomy.

: Robotic thyroidectomy via the bilateral axillo-breast approach (BABA), first introduced in Korea in 2008, has become a standard method of thyroid re...

Diagnosing thyroid nodules with atypia of undetermined significance/follicular lesion of undetermined significance cytology with the deep convolutional neural network.

To compare the diagnostic performances of physicians and a deep convolutional neural network (CNN) predicting malignancy with ultrasonography images o...

Machine learning methods for automated classification of tumors with papillary thyroid carcinoma-like nuclei: A quantitative analysis.

When approaching thyroid gland tumor classification, the differentiation between samples with and without "papillary thyroid carcinoma-like" nuclei is...

Transoral robotic resection of a lingual thyroid: a novel treatment for obstructive sleep apnoea.

A 34-year-old woman with a history of congenital hypothyroidism and 15 years of obstructive sleep apnoea was admitted with a left submandibular swelli...

Weakly supervised learning on unannotated H&E-stained slides predicts BRAF mutation in thyroid cancer with high accuracy.

Deep neural networks (DNNs) that predict mutational status from H&E slides of cancers can enable inexpensive and timely precision oncology. Although e...

Hyperthyroidism treatment by alternative therapies based on cupping and dietary-herbal supplementation: a case report.

OBJECTIVES: Hyperthyroidism is characterized by increasing production of thyroid hormone (TH) and decreasing of thyroid stimulation hormone (TSH) secr...

Application of Pet-CT Fusion Deep Learning Imaging in Precise Radiotherapy of Thyroid Cancer.

This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, studies its ability to distinguish benign and maligna...

A stacking ensemble deep learning approach to cancer type classification based on TCGA data.

Cancer tumor classification based on morphological characteristics alone has been shown to have serious limitations. Breast, lung, colorectal, thyroid...

Using deep learning to identify the recurrent laryngeal nerve during thyroidectomy.

Surgeons must visually distinguish soft-tissues, such as nerves, from surrounding anatomy to prevent complications and optimize patient outcomes. An a...

Prediction model for thyrotoxic atrial fibrillation: a retrospective study.

BACKGROUND: Thyrotoxic atrial fibrillation (TAF) is a recognized significant complication of hyperthyroidism. Early identification of the individuals ...