Applications of machine learning and deep learning to thyroid imaging: where do we stand?
Ultrasonography
; : 23-29, 2021.
Article
en En
| WPRIM
| ID: wpr-919505
Biblioteca responsable:
WPRO
ABSTRACT
Ultrasonography (US) is the primary diagnostic tool used to assess the risk of malignancy and to inform decision-making regarding the use of fine-needle aspiration (FNA) and postFNA management in patients with thyroid nodules. However, since US image interpretation is operator-dependent and interobserver variability is moderate to substantial, unnecessary FNA and/or diagnostic surgery are common in practice. Artificial intelligence (AI)-based computeraided diagnosis (CAD) systems have been introduced to help with the accurate and consistent interpretation of US features, ultimately leading to a decrease in unnecessary FNA. This review provides a developmental overview of the AI-based CAD systems currently used for thyroid nodules and describes the future developmental directions of these systems for the personalized and optimized management of thyroid nodules.
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WPRIM
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En
Revista:
Ultrasonography
Año:
2021
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Article