ArticleAJNR. American journal of neuroradiology2020
Radiomics Study of Thyroid Ultrasound for Predicting
Article in AJNR. American journal of neuroradiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.
- The Diagnostic Performance of Ultrasonography in the Evaluation of Extrathyroidal Extension in Papillary Thyroid Carcinoma: A Systematic Review and Meta-Analysis.International journal of molecular sciences · 2022Pooled it
- EnhancingQuantitative imaging in medicine and surgery · 2026Article
- Predictive Factors for Distant Metastasis in Follicular Thyroid Carcinoma: Analysis of Clinical, Genetic, and Radiomics Features.Journal of the Korean Society of Radiology · 2026Article
- Bilateral disease in the classic subtype of papillary thyroid carcinoma: clinical significance and development of an artificial intelligence-based multimodal prediction model.Frontiers in endocrinology · 2026Article
- Radiotranscriptomics in papillary thyroid carcinoma complement current noninvasive risk stratification system.Science advances · 2025Article
- Prediction of BRAF and TERT status in PTCs by machine learning-based ultrasound radiomics methods: A multicenter study.Journal of clinical & translational endocrinology · 2025Article
- Deep learning model based on ultrasound images predicts BRAF V600E mutation in papillary thyroid carcinoma.iScience · 2025Article
- Breaking barriers: noninvasive AI model for BRAFInternational journal of computer assisted radiology and surgery · 2025Article
- The Predictive Value of a Nomogram Based on Ultrasound Radiomics, Clinical Factors, and Enhanced Ultrasound Features for Central Lymph Node Metastasis in Papillary Thyroid Microcarcinoma.Ultrasonic imaging · 2025Article
- Ultrasound-based radiogenomics: status, applications, and future direction.Ultrasonography (Seoul, Korea) · 2025Article
- Nomogram model based on ultrasonography and contrast-enhanced CT for predicting BRAFFrontiers in endocrinology · 2025Article
- CT-based texture analysis predicts BRAFFrontiers in oncology · 2025Article
- Application progress of artificial intelligence in managing thyroid disease.Frontiers in endocrinology · 2025Review
- Integrating Deep Learning and Radiomics in Differentiating Papillary Thyroid Microcarcinoma from Papillary Thyroid Carcinoma with Ultrasound Images.Cancer management and research · 2025Article
- Multimodal MRI Deep Learning for Predicting Central Lymph Node Metastasis in Papillary Thyroid Cancer.Cancers · 2024Article
- Combined model integrating clinical, radiomics, BRAFGland surgery · 2024Article
- Ultrasound features as predictive markers ofGland surgery · 2024Article
- Combining radiomics with thyroid imaging reporting and data system to predict lateral cervical lymph node metastases in medullary thyroid cancer.BMC medical imaging · 2024Article
- Article
- Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases.Frontiers in molecular biosciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeIt is not known how radiomics using ultrasound images contribute to the detection of BRAF mutation. This study aimed to evaluate whether a radiomics study of gray-scale ultrasound can predict the presence or absence of MATERIALS AND
methodsThe study retrospectively included 96 thyroid nodules that were surgically confirmed papillary thyroid cancers between January 2012 and June 2013.
resultsThe incidence of high-suspicion nodules diagnosed on ultrasound was higher in the
conclusionsRadiomics study using thyroid sonography is limited in predicting the
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.