ArticleKorean journal of radiology2020
Computer-Aided Diagnosis System for the Evaluation of Thyroid Nodules on Ultrasonography: Prospective Non-Inferiority Study according to the Experience Level of Radiologists.
Article in Korean journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 31 citations in OpenAlex.
- A comparison of artificial intelligence versus radiologists in the diagnosis of thyroid nodules using ultrasonography: a systematic review and meta-analysis.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2022Pooled it
- Diagnostic accuracy of S-Detect in distinguishing benign and malignant thyroid nodules: A meta-analysis.PloS one · 2022Pooled it
- Human-AI collaboration for ultrasound diagnosis of thyroid nodules: a clinical trial.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2025Trial
- Ultrasonographic Evaluation of Pediatric Thyroid Nodules: Adult Risk Stratification Systems, 2021 K-TIRADS Revision, and Future Refinements.Korean journal of radiology · 2026Review
- Multiparametric ultrasound techniques are superior to AI-assisted ultrasound for assessment of solid thyroid nodules: a prospective study.Endocrine · 2025Article
- Enhancing diagnostic precision for thyroid C-TIRADS category 4 nodules: a hybrid deep learning and machine learning model integrating grayscale and elastographic ultrasound features.Quantitative imaging in medicine and surgery · 2025Article
- SWE, C-TIRADS and AI-assisted diagnostic systems in distinguishing thyroid nodules of different lesion size: Which has better diagnostic performance?Frontiers in endocrinology · 2025Article
- Ultrasonic radiomics in predicting pathologic type for thyroid cancer: a preliminary study using radiomics features for predicting medullary thyroid carcinoma.Frontiers in endocrinology · 2025Article
- Improving the diagnostic performance of inexperienced readers for thyroid nodules through digital self-learning and artificial intelligence assistance.Frontiers in endocrinology · 2024Article
- Clinical value of artificial intelligence in thyroid ultrasound: a prospective study from the real world.European radiology · 2023Article
- Artificial Intelligence for Pre-operative Diagnosis of Malignant Thyroid Nodules Based on Sonographic Features and Cytology Category.World journal of surgery · 2023Article
- Comparison of S-Detect and thyroid imaging reporting and data system classifications in the diagnosis of cytologically indeterminate thyroid nodules.Frontiers in endocrinology · 2023Article
- Artificial intelligence in thyroid ultrasound.Frontiers in oncology · 2023Review
- Machine Learning-Aided Chronic Kidney Disease Diagnosis Based on Ultrasound Imaging Integrated with Computer-Extracted Measurable Features.Journal of digital imaging · 2022Article
- [Value of ultrasonic S-Detect technique in diagnosis of breast masses].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2022Article
- Investigating the diagnostic efficiency of a computer-aided diagnosis system for thyroid nodules in the context of Hashimoto's thyroiditis.Frontiers in oncology · 2022Article
- Reliability of a computer-aided system in the evaluation of indeterminate ultrasound images of thyroid nodules.European thyroid journal · 2022Article
- Diagnosing thyroid nodules with atypia of undetermined significance/follicular lesion of undetermined significance cytology with the deep convolutional neural network.Scientific reports · 2021Observational
- Applications of machine learning and deep learning to thyroid imaging: where do we stand?Ultrasonography (Seoul, Korea) · 2021Article
- S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules.Journal of clinical medicine · 2020Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo determine whether a computer-aided diagnosis (CAD) system for the evaluation of thyroid nodules is non-inferior to radiologists with different levels of experience. MATERIALS AND
methodsPatients with thyroid nodules with a decisive diagnosis of benign or malignant nodule were consecutively enrolled from November 2017 to September 2018. Three radiologists with different levels of experience (1 month, 4 years, and 7 years) in thyroid ultrasound (US) reviewed the thyroid US with and without using the CAD system. Statistical analyses included non-inferiority testing of the diagnostic accuracy for malignant thyroid nodules between the CAD system and the three radiologists with a non-inferiority margin of 10%, comparison of the diagnostic performance, and the added value of the CAD system to the radiologists.
resultsAltogether, 197 patients were included in the study cohort. The diagnostic accuracy of the CAD system (88.48%, 95% confidence interval [CI] = 82.65-92.53) was non-inferior to that of the radiologists with less experience (1 month and 4 year) of thyroid US (83.03%, 95% CI = 76.52-88.02;
conclusionThe CAD system may offer support for decision-making in the diagnosis of malignant thyroid nodules for operators who have less experience with thyroid US.
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Registered trials
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