Thyroid

Development of a risk prediction model for second primary thyroid cancer in female breast cancer patients based on machine learning algorithms.

Female breast cancer patients remain at risk of developing additional primary cancers even following surgical treatment. Second primary thyroid cancer (SPTC) is the most common type of multiple primary cancer (MPC) in this demographic during their survivorship period, significantly burdening patients' quality of life. This study aimed to develop a risk prediction model for the occurrence of SPTC i...

Trajectory excited-state dynamics study of pyrazine: Assessment of potential energy surfaces and simulation of picosecond timescales.

The femtosecond and picosecond excited-state dynamics of pyrazine are studied using full-dimensional trajectory surface hopping (TSH) dynamics simulations. We assess how different types of potential energy surfaces (PESs) influence the simulated dynamics; these include on-the-fly potentials vs those obtained by the linear vibronic coupling (LVC) model, calculated by multistate multiconfigurational...

Artificial Intelligence-Enabled Analysis of Radiology Reports: Epidemiology and Outcomes of Incidental Thyroid Findings.

CONTEXT: Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, an...

Deep learning-based multimodal radiopathomics for preoperative prediction of lymph node metastasis in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) exhibits a high incidence and a strong propensity for lymph node metastasis (LNM). Accurate preoperative assessment ...

Leveraging routine clinical data for dementia risk prediction using machine learning.

BackgroundEarly diagnosis of dementia is essential for enabling timely interventions that may slow disease progression, improve patient outcomes, and ...

Marker-Free, Automated Eyelid Assessment in Thyroid Eye Disease Using Artificial Intelligence: A Multicenter Validation Study.

OBJECTIVE: To validate "Glandy LID," a novel marker-free, deep learning-based software designed for the automated assessment of eyelid morphology usin...

Identification and molecular typing of disulfidptosis-related biomarkers in anaplastic thyroid carcinoma.

Increasing evidence suggests that disulfidptosis plays a crucial role in tumorigenesis and progression. This study aimed to identify biomarkers closel...

ThyroFusion: A Multi-modal Deep Learning Framework Integrating Vision and Language for Thyroid Nodule Malignancy Risk Assessment.

Accurate differentiation between benign and malignant thyroid nodules remains challenging in clinical practice. Current deep learning approaches predo...

An Interpretable Machine-Learning Model for Predicting Occult Central Lymph Node Metastasis in Papillary Thyroid Cancer.

CONTEXT: Accurate preoperative prediction of occult lymph node metastasis (OLNM) in clinically lymph node negative (cN0) papillary thyroid carcinoma (...

Graves' disease: a new era of pathophysiology-guided therapeutics.

Graves' disease (GD) is an autoimmune entity that had an unchanged treatment paradigm for more than half a century with radioactive iodine, antithyroi...

A Comparative Assessment of Large Language Models in Congenital Hypothyroidism: Reliability, Quality and Readability.

OBJECTIVE: To comparatively evaluate the reliability, quality, and readability of responses generated by widely used large language model (LLM)-based ...

A hybrid CNN-XLSTM-GRU deep learning model with autoencoder-based feature selection for hypothyroidism diagnosis.

Hypothyroidism, caused by reduced thyroid-hormone production, is often difficult to diagnose because its symptoms are non-specific and overlap with ot...

Predictive models for the occurrence and lymph node metastasis of papillary thyroid carcinoma with regional risk heterogeneity.

Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, and cervical lymph node metastasis significantly impacts patient prognosis. T...

Diagnostic Accuracy of Ultrasound Radiomics for Cervical Lymph-Node Metastasis in Papillary Thyroid Carcinoma: Evidence Predominantly From Chinese Cohorts.

Pre-operative identification of cervical lymph-node metastasis (LNM) guides surgical extent in papillary thyroid carcinoma (PTC) but remains imperfect...

A vision-language foundation model improves preoperative diagnosis of follicular thyroid neoplasms using ultrasound images.

Preoperative discrimination between follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) remains challenging, as imaging and cytolo...

Region-guided decoupled fusion network for ultrasound-based classification of thyroid nodules with and without Hashimoto's thyroiditis.

RATIONALE AND OBJECTIVES: Differentiating benign from malignant thyroid nodules is particularly challenging in patients with Hashimoto's thyroiditis (...

Deep Learning-Based Multimodal Fusion of Ultrasound, Cytology, and Clinical Features to Distinguish Follicular Thyroid Carcinoma from Adenoma: A Multicenter Study.

RATIONALE AND OBJECTIVES: Preoperative differentiation between follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) remains challen...

Exploring Metabolic Changes in Children with Congenital Hypothyroidism: A Serum Metabolomic Study Combined by Machine Learning.

Congenital hypothyroidism (CH) is a genetic endocrine disorder that can cause developmental delays if it is untreated. In this study, NMR-based metabo...

Wooden-Tip Electrospray Ionization Mass Spectrometry Combined With Machine Learning for Differentiating Thyroid Tumours.

Direct mass spectrometry (MS) analysis of human tissues at the molecular level has great potential for clinical diagnosis and biomarker discovery. How...

Ultrasound Radiomics for Hashimoto's Thyroiditis: State of the Art and Future Perspectives.

Ultrasound radiomics is gradually emerging as a powerful tool for improving the diagnosis and management of Hashimoto's thyroiditis (HT), effectively ...