Endocrinology

Thyroid

Latest AI and machine learning research in thyroid for healthcare professionals.

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Transcriptomic profiling and machine learning reveal novel RNA signatures for enhanced molecular characterization of Hashimoto's thyroiditis.

While ultrasonography effectively diagnoses Hashimoto's thyroiditis (HT), exploring its transcriptom...

Artificial Intelligence and Whole Slide Imaging Assist in Thyroid Indeterminate Cytology: A Systematic Review.

INTRODUCTION: Thyroid cytopathology, particularly in cases of atypia of undetermined significance/fo...

Attention-based image segmentation and classification model for the preoperative risk stratification of thyroid nodules.

BACKGROUND: Despite widespread use of standardized classification systems, risk stratification of th...

Histopathological domain adaptation with generative adversarial networks: Bridging the domain gap between thyroid cancer histopathology datasets.

Deep learning techniques are increasingly being used to classify medical imaging data with high accu...

Predicting lymph node metastasis in thyroid cancer: systematic review and meta-analysis on the CT/MRI-based radiomics and deep learning models.

BACKGROUND: Thyroid cancer, a common endocrine malignancy, has seen increasing incidence, making lym...

The Effect of Intravenous Lidocaine on EC50 of Remifentanil for Preventing Cough During Emergence in Female for Thyroid Surgery Anesthesia.

OBJECTIVE: To evaluate the effect of intravenous lidocaine injection on the half-maximum effective c...

Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases.

Thyroid diseases, including functional and neoplastic diseases, bring a huge burden to people's heal...

Identification and verification of the optimal feature genes of ferroptosis in thyroid-associated orbitopathy.

BACKGROUND: Thyroid-associated orbitopathy (TAO) is an autoimmune inflammatory disorder of the orbit...

Linsitinib inhibits proliferation and induces apoptosis of both IGF-1R and TSH-R expressing cells.

BACKGROUND: The insulin-like growth factor 1 receptor (IGF-1R) and the thyrotropin receptor (TSH-R) ...

Enhancing Thyroid Pathology With Artificial Intelligence: Automated Data Extraction From Electronic Health Reports Using RUBY.

PURPOSE: Thyroid nodules are common in the general population, and assessing their malignancy risk i...

Subclinical/overt hypothyroidism may be associated with diminished ovarian reserve in infertile women independent of thyroid autoimmunity.

OBJECTIVE: To investigate the association between thyroid dysfunction or thyroid autoimmunity (TAI) ...

Potential impact of organophosphate esters on thyroid eye disease based on machine learning and molecular docking.

Organophosphate esters (OPEs) are widely used as flame retardants and plasticizers in daily commodit...

Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models.

Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hype...

Multiple-Instance Learning for thyroid gland disease classification: A hands-on experience.

The morphological diagnosis of thyroid gland neoplasms presents a dual challenge: it requires the ex...

The added value of including thyroid nodule features into large language models for automatic ACR TI-RADS classification based on ultrasound reports.

OBJECTIVE: The ACR Thyroid Imaging, Reporting, and Data System (TI-RADS) uses a score based on ultra...

An ultrasonography of thyroid nodules dataset with pathological diagnosis annotation for deep learning.

Ultrasonography (US) of thyroid nodules is often time consuming and may be inconsistent between obse...

TIRADS-based artificial intelligence systems for ultrasound images of thyroid nodules: protocol for a systematic review.

PURPOSE: The thyroid imaging reporting and data system (TIRADS) was developed as a standard global t...

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