AIMC Topic: Thyroid Neoplasms

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Identification of thyroid cancer biomarkers using WGCNA and machine learning.

European journal of medical research
OBJECTIVE: The incidence of thyroid cancer (TC) is increasing in China, largely due to overdiagnosis from widespread screening and improved ultrasound technology. Identifying precise TC biomarkers is crucial for accurate diagnosis and effective treat...

An Early Thyroid Screening Model Based on Transformer and Secondary Transfer Learning for Chest and Thyroid CT Images.

Technology in cancer research & treatment
IntroductionThyroid cancer is a common malignant tumor, and early diagnosis and timely treatment are crucial to improve patient prognosis. With the increasing use of enhanced CT scans, a new opportunity for early thyroid cancer screening has emerged....

Can Artificial Intelligence Software be Utilised for Thyroid Multi-Disciplinary Team Outcomes?

Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
OBJECTIVES: ChatGPT is one of the most publicly available artificial intelligence (AI) softwares. Ear, nose and throat (ENT) services are often stretched due to the increasing incidence of thyroid malignancies. This study aims to investigate whether ...

Interpretable machine learning for thyroid cancer recurrence predicton: Leveraging XGBoost and SHAP analysis.

European journal of radiology
PURPOSE: For patients suffering from differentiated thyroid cancer (DTC), several clinical, laboratory, and pathological features (including patient age, tumor size, extrathyroidal extension, or serum thyroglobulin levels) are currently used to ident...

ELTIRADS framework for thyroid nodule classification integrating elastography, TIRADS, and radiomics with interpretable machine learning.

Scientific reports
Early detection of malignant thyroid nodules is crucial for effective treatment, but traditional diagnostic methods face challenges such as variability in expert opinions and limited integration of advanced imaging techniques. This prospective cohort...

Prediction of peripheral lymph node metastasis (LNM) in thyroid cancer using delta radiomics derived from enhanced CT combined with multiple machine learning algorithms.

European journal of medical research
OBJECTIVES: This study aimed to develop a model for predicting peripheral lymph node metastasis (LNM) in thyroid cancer patients by combining enhanced CT radiomic features with machine learning algorithms. It increased the clinical utility and interp...

Diagnostic value of deep learning of multimodal imaging of thyroid for TI-RADS category 3-5 classification.

Endocrine
BACKGROUND: Thyroid nodules classified within the Thyroid Imaging Reporting and Data Systems (TI-RADS) category 3-5 are typically regarded as having varying degrees of malignancy risk, with the risk increasing from TI-RADS 3 to TI-RADS 5. While some ...

Development of disease diagnosis technology based on coattention cross-fusion of multiomics data.

Analytica chimica acta
BACKGROUND: Early diagnosis is vital for increasing the rates of curing diseases and patient survival in medicine. With the advancement of biotechnology, the types of bioomics data are increasing. The integration of multiomics data can provide more c...

Advanced pathological subtype classification of thyroid cancer using efficientNetB0.

Diagnostic pathology
BACKGROUND: Thyroid cancer is a prevalent malignancy requiring accurate subtype identification for effective treatment planning and prognosis evaluation. Deep learning has emerged as a valuable tool for analyzing tumor microenvironment features and d...

Emerging insights into thyroid cancer from immunotherapy perspective: A correspondence.

Human vaccines & immunotherapeutics
While recent studies, such as Wang et al. have explored immunotherapy trends in thyroid cancer, methodological limitations in data retrieval persist. To address this, we implemented a refined search strategy using the Web of Science Core Collection, ...