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Articles Published Processes
9/9/2026 9:45:17 AM | Browse: 3 | Download: 1
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Received |
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2025-12-08 01:27 |
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Peer-Review Started |
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2025-12-08 01:28 |
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First Decision by Editorial Office Director |
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2026-01-14 02:52 |
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Return for Revision |
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2026-01-14 02:52 |
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Revised |
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2026-01-26 06:48 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-03-02 02:44 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-03-02 10:11 |
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Articles in Press |
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2026-03-02 10:11 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-08-21 09:28 |
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Publish the Manuscript Online |
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2026-09-09 09:45 |
| 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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Oncology |
| Manuscript Type |
Opinion Review |
| Article Title |
Interpretable extracellular vesicle long RNA framework for noninvasive pancreatic cancer diagnosis: A multi-omics artificial intelligence-driven liquid biopsy paradigm
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Chang Yuan, Rong Hu and Sheng-Chun Dang |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Social Development Project of Zhenjiang City |
No. SH2024061 |
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| Corresponding Author |
Sheng-Chun Dang, Professor, Department of General Surgery, The Affiliated Hospital of Jiangsu University, No. 438 Jiefang Road, Zhenjiang 212000, Jiangsu Province, China. dscgu@163.com |
| Key Words |
Pancreatic ductal adenocarcinoma; Extracellular vesicles; Long RNA; Interpretable artificial intelligence; Liquid biopsy; Multi-omics integration; Machine learning |
| Core Tip |
We examine the ECD-itMLF interpretable machine learning model, which recently achieved a remarkable AUC of 0.9698 for early pancreatic ductal adenocarcinoma (PDAC) detection using sparse extracellular vesicle (EV) long RNA data. Despite this excellent performance, moving the tool into the clinic requires testing it against common patient variables like diabetes and jaundice. In this piece, we break down the model's explainable AI roots and present visual summaries of current multi-omics research. Looking ahead, we discuss how this EV-based approach could be adapted for tracking minimal residual disease (MRD) and integrating multiple analytes, providing a realistic path from the lab to everyday precision oncology. |
| Publish Date |
2026-09-09 09:45 |
| Citation |
Yuan C, Hu R, Dang SC. Interpretable extracellular vesicle long RNA framework for noninvasive pancreatic cancer diagnosis: A multi-omics artificial intelligence-driven liquid biopsy paradigm. World J Gastrointest Oncol 2026; 18(9): 117360
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| URL |
https://www.wjgnet.com/1948-5204/full/v18/i9/117360.htm |
| DOI |
https://doi.org/10.4251/wjgo.117360 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.
