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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2024.9
- 수록면
- 475 - 481 (7page)
- DOI
- 10.3342/kjorl-hns.2024.00010
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초록· 키워드
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The rapid progress in artificial intelligence (AI) technologies has made a significant impact onmedical image analysis, particularly in cancer diagnosis. The integration of AI algorithms intohistopathological image analysis holds promise for enhancing precision and efficiency in cancerdiagnosis. This review provides an in-depth analysis of recent developments in AI methodologies,including deep learning approaches applied to the interpretation of histopathologicalimages specific to head and neck cancer (HNC). Furthermore, it discusses the challengesand opportunities associated with the implementation of AI in this domain, such as data variability,interpretability, and clinical integration. Through this overview of current researchfindings, we aim to offer valuable insights on the state-of-the-art AI technologies, their potentialimpact on clinical practice, and future directions for advancing the field of HNC histopathologicalimage analysis.
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