Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Deep Learning Technology for Classification of Thyroid Nodules Using Multi-View Ultrasound Images: Potential Benefits and Challenges in Clinical Application
8
Zitationen
12
Autoren
2025
Jahr
Abstract
CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.
Ähnliche Arbeiten
2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer
2015 · 16.122 Zit.
Revised American Thyroid Association Management Guidelines for Patients with Thyroid Nodules and Differentiated Thyroid Cancer
2009 · 6.724 Zit.
Serum TSH, T<sub>4</sub>, and Thyroid Antibodies in the United States Population (1988 to 1994): National Health and Nutrition Examination Survey (NHANES III)
2002 · 3.836 Zit.
Increasing Incidence of Thyroid Cancer in the United States, 1973-2002
2006 · 3.353 Zit.
Integrated Genomic Characterization of Papillary Thyroid Carcinoma
2014 · 3.018 Zit.