BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
1/12/2026 10:07:38 AM | Browse: 0 | Download: 0
 |
Received |
|
2025-07-01 01:07 |
|
Peer-Review Started |
|
2025-07-01 01:07 |
|
First Decision by Editorial Office Director |
|
2025-07-25 07:53 |
|
Return for Revision |
|
2025-07-26 07:02 |
|
Revised |
|
2025-08-15 21:08 |
 |
Publication Fee Transferred |
|
|
|
Second Decision by Editor |
|
2025-11-24 02:39 |
|
Second Decision by Editor-in-Chief |
|
|
|
Final Decision by Editorial Office Director |
|
2025-11-24 07:07 |
|
Articles in Press |
|
2025-11-24 07:07 |
|
Edit the Manuscript by Language Editor |
|
|
|
Typeset the Manuscript |
|
2026-01-03 12:53 |
|
Publish the Manuscript Online |
|
2026-01-12 10:07 |
| ISSN |
1948-5204 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
|
| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
|
| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| 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 |
| ORCID |
|
| 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. |
| Publish Date |
2026-01-12 10:07 |
| 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 2026; 18(1): 111357 |
| URL |
https://www.wjgnet.com/1948-5204/full/v18/i1/111357.htm |
| DOI |
https://dx.doi.org/10.4251/wjgo.v18.i1.111357 |
© 2004-2026 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
California Corporate Number: 3537345
