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Thyroid Diseases

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Robot-assisted transaxillary thyroidectomy: surgical technique.

European annals of otorhinolaryngology, head and neck diseases
Robot-assisted transaxillary thyroid surgery avoids the need for a neck incision. It consists of thyroid lobectomy and isthmectomy for moderately large unilateral benign nodules. The surgical imperatives are the same as for conventional surgery, but ...

A novel maternal thyroid disease prediction using multi-scale vision transformer architecture with improved linguistic hedges neural-fuzzy classifier.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Early pregnancy thyroid function assessment in mothers is covered. The benefits of using load-specific reference ranges are well-established.

[Review on ultrasonographic diagnosis of thyroid diseases based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In recent years, the incidence of thyroid diseases has increased significantly and ultrasound examination is the first choice for the diagnosis of thyroid diseases. At the same time, the level of medical image analysis based on deep learning has been...

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

BMC medical imaging
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...

Ensemble machine learning for the prediction of patient-level outcomes following thyroidectomy.

American journal of surgery
BACKGROUND: Accurate prediction of thyroidectomy complications is necessary to inform treatment decisions. Ensemble machine learning provides one approach to improve prediction.

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

Scientific reports
Surgeons must visually distinguish soft-tissues, such as nerves, from surrounding anatomy to prevent complications and optimize patient outcomes. An accurate nerve segmentation and analysis tool could provide useful insight for surgical decision-maki...

Deep learning for intelligent diagnosis in thyroid scintigraphy.

The Journal of international medical research
OBJECTIVE: To construct deep learning (DL) models to improve the accuracy and efficiency of thyroid disease diagnosis by thyroid scintigraphy.

Rapid Screening of Thyroid Dysfunction Using Raman Spectroscopy Combined with an Improved Support Vector Machine.

Applied spectroscopy
This study aimed to screen for thyroid dysfunction using Raman spectroscopy combined with an improved support vector machine (SVM). In spectral analysis, in order to further improve the classification accuracy of the SVM algorithm model, a genetic pa...

A Study on the Auxiliary Diagnosis of Thyroid Disease Images Based on Multiple Dimensional Deep Learning Algorithms.

Current medical imaging
BACKGROUND: Medical imaging plays an important role in the diagnosis of thyroid diseases. In the field of machine learning, multiple dimensional deep learning algorithms are widely used in image classification and recognition, and have achieved great...

Thyroid disorders in obese patients. Does insulin resistance make a difference?

Archives of endocrinology and metabolism
OBJECTIVE: The aim of this study was to evaluate the association between insulin resistance and thyroid pathology in obese patients, and compare the results between insulin-resistant and noninsulin-resistant patients.