Current Developments of Artificial Intelligences in Head and Neck Cancer Histopathological Images Analysis
10.3342/kjorl-hns.2024.00010
- Author:
Young Chan LEE
1
Author Information
1. Department of Otolaryngology-Head and Neck Surgery, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul, Korea
- Publication Type:Review
- From:Korean Journal of Otolaryngology - Head and Neck Surgery
2024;67(9):475-481
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
The rapid progress in artificial intelligence (AI) technologies has made a significant impact on medical image analysis, particularly in cancer diagnosis. The integration of AI algorithms into histopathological image analysis holds promise for enhancing precision and efficiency in cancer diagnosis. This review provides an in-depth analysis of recent developments in AI methodologies, including deep learning approaches applied to the interpretation of histopathological images specific to head and neck cancer (HNC). Furthermore, it discusses the challenges and opportunities associated with the implementation of AI in this domain, such as data variability, interpretability, and clinical integration. Through this overview of current research findings, we aim to offer valuable insights on the state-of-the-art AI technologies, their potential impact on clinical practice, and future directions for advancing the field of HNC histopathological image analysis.
