Cited 31 times in
Deep Learning-Based Artificial Intelligence for Mammography
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김은경 | - |
dc.contributor.author | 윤정현 | - |
dc.date.accessioned | 2021-09-29T01:55:25Z | - |
dc.date.available | 2021-09-29T01:55:25Z | - |
dc.date.issued | 2021-08 | - |
dc.identifier.issn | 1229-6929 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/184619 | - |
dc.description.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. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | Korean Society of Radiology | - |
dc.relation.isPartOf | KOREAN JOURNAL OF RADIOLOGY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Deep Learning-Based Artificial Intelligence for Mammography | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Radiology (영상의학교실) | - |
dc.contributor.googleauthor | Jung Hyun Yoon | - |
dc.contributor.googleauthor | Eun Kyung Kim | - |
dc.identifier.doi | 10.3348/kjr.2020.1210 | - |
dc.contributor.localId | A00801 | - |
dc.contributor.localId | A02595 | - |
dc.relation.journalcode | J02884 | - |
dc.identifier.eissn | 2005-8330 | - |
dc.identifier.pmid | 33987993 | - |
dc.subject.keyword | Artificial intelligence | - |
dc.subject.keyword | Breast cancer | - |
dc.subject.keyword | Computer-aided diagnosis | - |
dc.subject.keyword | Deep learning | - |
dc.subject.keyword | Mammography | - |
dc.contributor.alternativeName | Kim, Eun Kyung | - |
dc.contributor.affiliatedAuthor | 김은경 | - |
dc.contributor.affiliatedAuthor | 윤정현 | - |
dc.citation.volume | 22 | - |
dc.citation.number | 8 | - |
dc.citation.startPage | 1225 | - |
dc.citation.endPage | 1239 | - |
dc.identifier.bibliographicCitation | KOREAN JOURNAL OF RADIOLOGY, Vol.22(8) : 1225-1239, 2021-08 | - |
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