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Deep Learning-Based Artificial Intelligence for Mammography
Korean Journal of Radiology ; : 1225-1239, 2021.
Article in English | WPRIM | ID: wpr-894722
ABSTRACT
During the past decade, researchers have investigated the use of computer-aided mammography interpretation. With the application of deep learning technology, artificial intelligence (AI)-based algorithms for mammography have shown promising results in the quantitative assessment of parenchymal density, detection and diagnosis of breast cancer, and prediction of breast cancer risk, enabling more precise patient management. AI-based algorithms may also enhance the efficiency of the interpretation workflow by reducing both the workload and interpretation time. However, more in-depth investigation is required to conclusively prove the effectiveness of AI-based algorithms. This review article discusses how AI algorithms can be applied to mammography interpretation as well as the current challenges in its implementation in real-world practice.
Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: English Journal: Korean Journal of Radiology Year: 2021 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: English Journal: Korean Journal of Radiology Year: 2021 Type: Article