Publication Name	World Journal of Gastrointestinal Oncology
Manuscript ID	111357
Country	Japan

Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Opportunities and challenges of artificial intelligence-assisted endoscopy and high-quality data for esophageal squamous cell carcinoma
Manuscript Source	Invited Manuscript
All Author List	Ken Kurisaki, Shinichiro Kobayashi, Taro Akashi, Yasuhiko Nakao, Masayuki Fukumoto, Kaito Tasaki, Tomohiko Adachi, Susumu Eguchi and Kengo Kanetaka
Funding Agency and Grant Number	Funding Agency Grant Number Japan Society for the Promotion of Science 24K11935
Corresponding Author	Shinichiro Kobayashi, Associate Professor, FACS, MD, PhD, Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8501, Japan. skobayashi1980@gmail.com
Key Words	Artificial intelligence; Esophageal cancer; Endoscopy; Deep learning; National database; Clinical translation; Multimodal artificial intelligence
Core Tip	This review detailed how artificial intelligence (AI) mitigates operator dependence in the endoscopic diagnosis of esophageal squamous cell carcinoma by comparing the sensitivity and specificity of innovative deep learning models with those of expert endoscopists. This further highlights the use of large-scale repositories, such as the National Clinical Database and Japan Endoscopy Database, for robust AI training and validation. Multimodal AI using big databases proposes a multi-institutional or multi-vendor AI strategy in Japan. Finally, we outlined future directions for real-time endoscopic support and the integration of clinical outcomes into next-generation AI-driven endoscopy.
Citation	Kurisaki K, Kobayashi S, Akashi T, Nakao Y, Fukumoto M, Tasaki K, Adachi T, Eguchi S, Kanetaka K. Opportunities and challenges of artificial intelligence-assisted endoscopy and high-quality data for esophageal squamous cell carcinoma. World J Gastrointest Oncol 2025; In press

Received	2025-07-01 01:07
Peer-Review Started	2025-07-01 01:07
To Make the First Decision
Return for Revision	2025-07-26 07:02
Revised	2025-08-15 21:08
Second Decision	2025-11-24 02:39
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-11-24 07:07
Articles in Press	2025-11-24 07:07
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Typeset the Manuscript

ISSN	1948-5204 (online)
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