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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.9
- 수록면
- 594 - 604 (11page)
- DOI
- 10.5946/ce.2021.229
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초록· 키워드
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Over the past decade, technological advances in deep learning have led to the introduction of artificial intelligence (AI) in medical im- aging. The most commonly used structure in image recognition is the convolutional neural network, which mimics the action of the human visual cortex. The applications of AI in gastrointestinal endoscopy are diverse. Computer-aided diagnosis has achieved remark- able outcomes with recent improvements in machine-learning techniques and advances in computer performance. Despite some hur- dles, the implementation of AI-assisted clinical practice is expected to aid endoscopists in real-time decision-making. In this summary, we reviewed state-of-the-art AI in the field of gastrointestinal endoscopy and offered a practical guide for building a learning image dataset for algorithm development.
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