ReviewFrontiers in oncology2023
The progress of radiomics in thyroid nodules.
Review in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 20 citations in OpenAlex.
- Ultrasound Radiomics for Hashimoto's Thyroiditis: State of the Art and Future Perspectives.Journal of clinical ultrasound : JCU · 2026Review
- Development and validation of an Automated computed tomography segmentation model for thyroid nodules using a channel attention high-resolution network.Gland surgery · 2026Article
- Application of transformer attention mechanism-based multimodal deep learning model in the diagnosis of papillary thyroid carcinoma.BMC medical imaging · 2026Article
- Machine Learning for diagnosis of malignant thyroid nodules based on thyroid ultrasound: Systematic review and meta-analysis of studies with external datasets.European journal of radiology open · 2026Article
- Article
- Diagnostic Performance of the ACR TI-RADS, C-TIRADS, K-TIRADS, and EU TI-RADS Classification Systems for Thyroid Micronodules: A Multicenter Prospective Study.International journal of general medicine · 2026Article
- Radiotranscriptomics in papillary thyroid carcinoma complement current noninvasive risk stratification system.Science advances · 2025Article
- Development and validation of a prediction model for lymph node metastasis in thyroid cancer: integrating deep learning and radiomics features from intra- and peri-tumoral regions.Gland surgery · 2025Article
- A nomogram for predicting the nature of thyroid adenomatoid nodules on ultrasound: a dual-center study.Frontiers in oncology · 2025Article
- Combined model integrating clinical, radiomics, BRAFGland surgery · 2024Article
- Review
- Multimodal Ultrasound Radiomic Technology for Diagnosing Benign and Malignant Thyroid Nodules of Ti-Rads 4-5: A Multicenter Study.Sensors (Basel, Switzerland) · 2024Article
- Article
- Combining radiomics with thyroid imaging reporting and data system to predict lateral cervical lymph node metastases in medullary thyroid cancer.BMC medical imaging · 2024Article
- CT-based radiomics features for the differential diagnosis of nodular goiter and papillary thyroid carcinoma: an analysis employing propensity score matching.Frontiers in oncology · 2024Article
- Radiomics-based ultrasound models for thyroid nodule differentiation in Hashimoto's thyroiditis.Frontiers in endocrinology · 2023Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to the development of Artificial Intelligence (AI), Machine Learning (ML), and the improvement of medical imaging equipment, radiomics has become a popular research in recent years. Radiomics can obtain various quantitative features from medical images, highlighting the invisible image traits and significantly enhancing the ability of medical imaging identification and prediction. The literature indicates that radiomics has a high potential in identifying and predicting thyroid nodules. So in this article, we explain the development, definition, and workflow of radiomics. And then, we summarize the applications of various imaging techniques in identifying benign and malignant thyroid nodules, predicting invasiveness and metastasis of thyroid lymph nodes, forecasting the prognosis of thyroid malignancies, and some new advances in molecular level and deep learning. The shortcomings of this technique are also summarized, and future development prospects are provided.
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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.