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Artificial intelligence in breast ultrasonography
- Kim, Jaeil;
- Kim, Hye Jung;
- Kim, Chanho;
- Kim, Won Hwa
WEB OF SCIENCE
39SCOPUS
48초록
Although breast ultrasonography is the mainstay modality for differentiating between benign and malignant breast masses, it has intrinsic problems with false positives and substantial interobserver variability. Artificial intelligence (AI), particularly with deep learning models, is expected to improve workflow efficiency and serve as a second opinion. AI is highly useful for performing three main clinical tasks in breast ultrasonography: detection (localization/segmentation), differential diagnosis (classification), and prognostication (prediction). This article provides a current overview of AI applications in breast ultrasonography, with a discussion of methodological considerations in the development of AI models and an up-to-date literature review of potential clinical applications.
키워드
- 제목
- Artificial intelligence in breast ultrasonography
- 저자
- Kim, Jaeil; Kim, Hye Jung; Kim, Chanho; Kim, Won Hwa
- 발행일
- 2021-04
- 유형
- Review
- 저널명
- Ultrasonography
- 권
- 40
- 호
- 2
- 페이지
- 183 ~ 190
- 언어
- ENG
- 출판사
- KOREAN SOC ULTRASOUND MEDICINE
- 발행국가
- 대한민국
- 분량
- 8 페이지
- ISSN
- E 2288-5943
P 2288-5919