AIMC Topic: Thyroid Neoplasms
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Breaking barriers: noninvasive AI model for BRAF mutation identification.
International journal of computer assisted radiology and surgery
Feb 15, 2025
OBJECTIVE: BRAF is the most common mutation found in thyroid cancer and is particularly associated with papillary thyroid carcinoma (PTC). Currently, genetic mutation detection relies on invasive procedures. This study aimed to extract radiomic featu...
Interpretable Machine Learning to Predict the Malignancy Risk of Follicular Thyroid Neoplasms in Extremely Unbalanced Data: Retrospective Cohort Study and Literature Review.
JMIR cancer
Feb 10, 2025
BACKGROUND: Diagnosing and managing follicular thyroid neoplasms (FTNs) remains a significant challenge, as the malignancy risk cannot be determined until after diagnostic surgery.
ThyroNet-X4 genesis: an advanced deep learning model for auxiliary diagnosis of thyroid nodules' malignancy.
Scientific reports
Feb 4, 2025
Thyroid nodules are a common endocrine condition, and accurate differentiation between benign and malignant nodules is essential for making appropriate treatment decisions. Traditional ultrasound-based diagnoses often depend on the expertise of physi...
Ultrasound and histopathological assessment of benign, borderline, and malignant thyroid tumors in pediatric patients: an illustrative review and literature overview.
Frontiers in endocrinology
Jan 30, 2025
BACKGROUND: The risk of malignancy in thyroid nodules is higher in children than in adults, often necessitating a more aggressive endocrine and surgical approach. However, given that not all solid thyroid nodules are malignant, a more conservative ap...
Machine Learning Model for Risk Stratification of Papillary Thyroid Carcinoma Based on Radiopathomics.
Academic radiology
Jan 26, 2025
RATIONALE AND OBJECTIVES: This study aims to develop a radiopathomics model based on preoperative ultrasound and fine-needle aspiration cytology (FNAC) images to enable accurate, non-invasive preoperative risk stratification for patients with papilla...
Deep Learning Technology for Classification of Thyroid Nodules Using Multi-View Ultrasound Images: Potential Benefits and Challenges in Clinical Application.
Endocrinology and metabolism (Seoul, Korea)
Jan 13, 2025
BACKGRUOUND: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules.
Construction of an anaplastic thyroid cancer stratification signature to guide immune therapy selection and validation of the pivotal gene HLF through experiments.
Frontiers in immunology
Jan 13, 2025
INTRODUCTION: While most thyroid cancer patients have a favorable prognosis, anaplastic thyroid carcinoma (ATC) remains a particularly aggressive form with a median survival time of just five months. Conventional therapies offer limited benefits for ...
Neural Network and Logistic Regression Models Based on Ultrasound Radiomics and Clinical-Pathological Features to Predict Occult Level II Lymph Node Metastasis in Papillary Thyroid Carcinoma.
Academic radiology
Jan 4, 2025
RATIONALE AND OBJECTIVES: Papillary thyroid carcinoma (PTC) often metastasizes to lateral cervical lymph nodes, especially in level II. This study aims to develop predictive models to identify level II lymph node metastasis (LNM), guiding selective n...
Artificial Intelligence and Whole Slide Imaging Assist in Thyroid Indeterminate Cytology: A Systematic Review.
Acta cytologica
Jan 2, 2025
INTRODUCTION: Thyroid cytopathology, particularly in cases of atypia of undetermined significance/follicular lesions of undetermined significance (AUS/FLUS), suffers from suboptimal sensitivity and specificity challenges. Recent advancements in digit...
A machine learning model utilizing Delphian lymph node characteristics to predict contralateral central lymph node metastasis in papillary thyroid carcinoma: a prospective multicenter study.
International journal of surgery (London, England)
Jan 1, 2025
BACKGROUND: This study aimed to use artificial intelligence (AI) to integrate various radiological and clinical pathological data to identify effective predictors of contralateral central lymph node metastasis (CCLNM) in patients with papillary thyro...
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