Publication Name	World Journal of Gastrointestinal Oncology
Manuscript ID	119847
Country	Türkiye

Category	Gastroenterology & Hepatology
Manuscript Type	Retrospective Cohort Study
Article Title	Interpretable multimodal artificial intelligence model for predicting advanced neoplasia in pancreatic cystic lesions
Manuscript Source	Unsolicited Manuscript
All Author List	Yavuz Özden, Ömer Yüzügülen and Ferhat Omurca
Funding Agency and Grant Number
Corresponding Author	Yavuz Özden, MD, Department of Gastroenterology, Kayseri City Hospital, University of Health Sciences, Şeker District, Muhsin Yazıcıoğlu Boulevard No. 77 Kocasinan, Kayseri 38080, Türkiye. yavuzozden@gmail.com
Key Words	Pancreatic cystic lesions; Artificial intelligence; Endoscopic ultrasound; Cyst fluid biomarkers; Intraductal papillary mucinous neoplasm; Risk stratification
Core Tip	Current guideline-based algorithms for pancreatic cystic lesions predominantly rely on morphology and show limited discrimination for advanced neoplasia. In this retrospective cohort study of 187 surgically resected lesions, we developed and internally validated an interpretable multimodal model integrating clinical variables, endoscopic ultrasound features, and cyst fluid biomarkers. The model achieved superior discrimination compared with international guideline criteria and demonstrated stable performance across key subgroups. This interpretable framework may support preoperative risk stratification, pending external validation.
Citation	Özden Y, Yüzügülen Ö, Omurca F. Interpretable multimodal artificial intelligence model for predicting advanced neoplasia in pancreatic cystic lesions. World J Gastrointest Oncol 2026; In press

Received	2026-02-07 03:15
Peer-Review Started	2026-02-07 03:17
First Decision by Editorial Office Director	2026-02-25 09:10
Return for Revision	2026-02-25 20:40
Revised	2026-02-28 20:11
Publication Fee Transferred	2026-03-13 10:29
Second Decision by Editor	2026-04-20 02:56
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-04-20 07:06
Articles in Press	2026-04-20 07:06
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1948-5204 (online)
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Copyright	©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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