ArticleCancers2019
The Diagnostic Efficiency of Ultrasound Computer-Aided Diagnosis in Differentiating Thyroid Nodules: A Systematic Review and Narrative Synthesis.
Article in Cancers, 2019. 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.
- Roadmap for Representative Artificial Intelligence Models for Thyroid Cancer.The Laryngoscope · 2026Review
- Artificial intelligence in thyroid ultrasound: clinical applications and perspectives.Frontiers in endocrinology · 2026Review
- Comparative diagnostic performance of C-TIRADS versus Kwak TI-RADS for thyroid nodules: implications for fine-needle aspiration biopsy referral.Frontiers in endocrinology · 2026Article
- Diagnostic performance of ultrasound S-Detect technology in evaluating BI-RADS-4 breast nodules ≤ 20 mm and > 20 mm.BMC cancer · 2025Article
- Article
- An ultrasound image segmentation method for thyroid nodules based on dual-path attention mechanism-enhanced UNet+.BMC medical imaging · 2024Article
- Study on diagnosis of thyroid nodules based on convolutional neural network.Radiologie (Heidelberg, Germany) · 2023Article
- Integration of Artificial Intelligence Decision Aids to Reduce Workload and Enhance Efficiency in Thyroid Nodule Management.JAMA network open · 2023Article
- Article
- Endocrine Tumor Classification via Machine-Learning-Based Elastography: A Systematic Scoping Review.Cancers · 2023Article
- The Future of Thyroid Nodule Risk Stratification.Endocrinology and metabolism clinics of North America · 2022Review
- Lack of Association BetweenFrontiers in cellular and infection microbiology · 2021Article
- Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size.Frontiers in molecular biosciences · 2021Article
- Visual Interpretability in Computer-Assisted Diagnosis of Thyroid Nodules Using Ultrasound Images.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules.Journal of clinical medicine · 2020Article
- Artificial Intelligence for Personalized Medicine in Thyroid Cancer: Current Status and Future Perspectives.Frontiers in oncology · 2020Review
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2 authors.
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Abstract
Computer-aided diagnosis (CAD) techniques have emerged to complement qualitative assessment in the diagnosis of benign and malignant thyroid nodules. The aim of this review was to summarize the current evidence on the diagnostic performance of various ultrasound CAD in characterizing thyroid nodules. PUBMED, EMBASE and Cochrane databases were searched for studies published until August 2019. The Quality Assessment of Studies of Diagnostic Accuracy included in Systematic Review 2 (QUADAS-2) tool was used to assess the methodological quality of the studies. Reported diagnostic performance data were analyzed and discussed. Fourteen studies with 2232 patients and 2675 thyroid nodules met the inclusion criteria. The study quality based on QUADAS-2 assessment was moderate. At best performance, grey scale CAD had a sensitivity of 96.7% while Doppler CAD was 90%. Combined techniques of qualitative grey scale features and Doppler CAD assessment resulted in overall increased sensitivity (92%) and optimal specificity (85.1%). The experience of the CAD user, nodule size and the thyroid malignancy risk stratification system used for interpretation were the main potential factors affecting diagnostic performance outcomes. The diagnostic performance of CAD of thyroid ultrasound is comparable to that of qualitative visual assessment; however, combined techniques have the potential for better optimized diagnostic accuracy.
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