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Thyroid Neoplasms

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AIBx, Artificial Intelligence Model to Risk Stratify Thyroid Nodules.

Thyroid : official journal of the American Thyroid Association
Current classification systems for thyroid nodules are very subjective. Artificial intelligence (AI) algorithms have been used to decrease subjectivity in medical image interpretation. One out of 2 women over the age of 50 years may have a thyroid n...

Robotic Transaxillary Hemithyroidectomy Using the da Vinci SP Robotic System: Initial Experience With 10 Consecutive Cases.

Surgical innovation
Many studies have shown the operative feasibility and safety of robotic thyroidectomy. However, there is still a concern on the operative invasiveness of robotic thyroidectomy owing to the wide flap dissection. The aim of this study was to introduce...

Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training.

European radiology
PURPOSE: This study aimed to validate a deep learning model's diagnostic performance in using computed tomography (CT) to diagnose cervical lymph node metastasis (LNM) from thyroid cancer in a large clinical cohort and to evaluate the model's clinica...

Application of a machine learning algorithm to predict malignancy in thyroid cytopathology.

Cancer cytopathology
BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) comprises 6 categories used for the diagnosis of thyroid fine-needle aspiration biopsy (FNAB). Each category has an associated risk of malignancy, which is important in the ...

Automatic cancer tissue detection using multispectral photoacoustic imaging.

International journal of computer assisted radiology and surgery
PURPOSE: In the case of multispecimen study to locate cancer regions, such as in thyroidectomy and prostatectomy, a significant labor-intensive processing is required at a high cost. Pathology diagnosis is usually done by a pathologist observing tiss...

Machine learning-based multiparametric MRI radiomics for predicting the aggressiveness of papillary thyroid carcinoma.

European journal of radiology
PURPOSE: To investigate the predictive capability of machine learning-based multiparametric magnetic resonance (MR) imaging radiomics for evaluating the aggressiveness of papillary thyroid carcinoma (PTC) preoperatively.

Classification and Diagnosis of Thyroid Carcinoma Using Reinforcement Residual Network with Visual Attention Mechanisms in Ultrasound Images.

Journal of medical systems
How to differentiate thyroid cancer nodules from a large number of benign nodules is always a challenging subject for clinicians. This paper proposes a novel Sal-deel network model to achieve the classification and diagnosis of thyroid cancer, which ...

High-Resolution Raman Microscopic Detection of Follicular Thyroid Cancer Cells with Unsupervised Machine Learning.

The journal of physical chemistry. B
We use Raman microscopic images with high spatial and spectral resolution to investigate differences between human follicular thyroid (Nthy-ori 3-1) and follicular thyroid carcinoma (FTC-133) cells, a well-differentiated thyroid cancer. Through compa...