AIMC Topic: Thyroid Cancer, Papillary

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A radiopathomics model for predicting large-number cervical lymph node metastasis in clinical N0 papillary thyroid carcinoma.

European radiology
OBJECTIVES: This study aimed to develop a multimodal radiopathomics model utilising preoperative ultrasound (US) and fine-needle aspiration cytology (FNAC) to predict large-number cervical lymph node metastasis (CLNM) in patients with clinically lymp...

Machine Learning Model for Risk Stratification of Papillary Thyroid Carcinoma Based on Radiopathomics.

Academic radiology
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...

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)
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...

Artificial intelligence-based multi-modal multi-tasks analysis reveals tumor molecular heterogeneity, predicts preoperative lymph node metastasis and prognosis in papillary thyroid carcinoma: a retrospective study.

International journal of surgery (London, England)
BACKGROUND: Papillary thyroid carcinoma (PTC) is the predominant form of thyroid cancer globally, especially when lymph node metastasis (LNM) occurs. Molecular heterogeneity, driven by genetic alterations and tumor microenvironment components, contri...

Deep learning based analysis of dynamic video ultrasonography for predicting cervical lymph node metastasis in papillary thyroid carcinoma.

Endocrine
BACKGROUND: Cervical lymph node metastasis (CLNM) is the most common form of thyroid cancer metastasis. Accurate preoperative CLNM diagnosis is of more importance in patients with papillary thyroid cancer (PTC). However, there is currently no unified...

Optimizing thyroid AUS nodules malignancy prediction: a comprehensive study of logistic regression and machine learning models.

Frontiers in endocrinology
BACKGROUND: The accurate diagnosis of thyroid nodules with indeterminate cytology, particularly in the atypia of undetermined significance (AUS) category, remains challenging. This study aims to predict the risk of malignancy in AUS nodules by compar...

Classifying driver mutations of papillary thyroid carcinoma on whole slide image: an automated workflow applying deep convolutional neural network.

Frontiers in endocrinology
BACKGROUND: Informative biomarkers play a vital role in guiding clinical decisions regarding management of cancers. We have previously demonstrated the potential of a deep convolutional neural network (CNN) for predicting cancer driver gene mutations...

Artificial intelligence-based pathological application to predict regional lymph node metastasis in Papillary Thyroid Cancer.

Current problems in cancer
In this study, a model for predicting lymph node metastasis in papillary thyroid cancer was trained using pathology images from the TCGA(The Cancer Genome Atlas) public dataset of papillary thyroid cancer, and a front-end inference model was trained ...

Explainable machine learning model for predicting paratracheal lymph node metastasis in cN0 papillary thyroid cancer.

Scientific reports
Prophylactic dissection of paratracheal lymph nodes in clinically lymph node-negative (cN0) papillary thyroid carcinoma (PTC) remains controversial. This study aims to integrate preoperative and intraoperative variables to compare traditional nomogra...