인공지능을 활용한 혀이미지 기반 암 진단의 해외 연구 동향 분석 : 스코핑리뷰

Abstract

Abstract Tongue diagnosis has been a primary tool for disease diagnosis in traditional medicine. With recent advances in artificial intelligence technology and efforts to objectify image analysis, this study aims to systematically organize research on AI-based tongue diagnosis image analysis. By comparing disease groups, applied technologies, and predictive performance, it seeks to present the international status of cancer diagnosis research and the clinical applicability for early cancer detection. This study collected literature from PubMed using the terms ‘Artificial Intelligence’, ‘Neoplasms’, ‘Tongue’, ‘image’, related MeSH terms, and free text. Disease groups included gastric cancer, oral cancer, lung cancer, and tongue cancer, with machine learning and deep learning techniques such as CNN, ResNet, U-Net, DBN, and CGTO employed. This review examines the potential application of artificial intelligence in tongue-based cancer diagnosis, aiming to suggest the direction for next-generation radiology and early cancer diagnosis.