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Articles in Press
11/12/2026 10:05:44 AM | Browse: 2 | Download: 0
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Minireviews |
| Article Title |
From prediction to intervention: Translating machine learning risk models into clinical decision support for gastric cancer surgery
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Wen-Li Wang, Jun Jiang and Hai-Qiang Wang |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Weifang City Science and Technology Development Plan (Medical Category) |
2023YX057 |
| Weifang Traditional Chinese Medicine Scientific Research Program |
WFZYY2025-3-018 |
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| Corresponding Author |
Jun Jiang, Operating Room, Affiliated Hospital of Shandong Second Medical University (Clinical Medical College), No. 2428 Yuhe Road, Kuiwen District, Weifang 261000, Shandong Province, China. fyjiangjun@sdsmu.edu.cn |
| Key Words |
Gastric cancer; Gastrectomy; Artificial intelligence; Clinical decision support systems; Machine learning; Postoperative complications; Anastomotic leakage; Implementation science |
| Core Tip |
Machine learning risk models for gastric cancer surgery increasingly predict complications with high reported discrimination, yet few reach the bedside. This narrative review synthesizes the translation gap across technical, clinical, organizational/regulatory, and ethical dimensions, clearly separating direct gastric-cancer evidence from indirect evidence from other settings, and proposes a conceptual five-stage framework — from clinical-need definition and intrinsically explainable design, through prospective multicenter validation with decision curve analysis and workflow-embedded user-centered prototyping, to post-deployment monitoring with continuous learning. Gradient-boosted models for delayed wound healing exemplify this gap, and a Danish colorectal cancer artificial intelligence implementation provides a benchmark; the field must shift from model-centric area under the receiver operating characteristic curve metrics to patient-centric, continuously evaluated decision support. |
| Citation |
Wang WL, Jiang J, Wang HQ. From prediction to intervention: Translating machine learning risk models into clinical decision support for gastric cancer surgery. World J Gastrointest Oncol 2026; In press
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| PDF |
127041-in-press.pdf
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Received |
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2026-08-20 07:25 |
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Peer-Review Started |
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2026-08-20 07:26 |
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First Decision by Editorial Office Director |
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Return for Revision |
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2026-09-29 00:38 |
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Revised |
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2026-10-08 03:30 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-11-12 05:53 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-11-12 10:05 |
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Articles in Press |
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2026-11-12 10:05 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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| ISSN |
1948-5204 (online) |
| Open Access |
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Copyright |
© The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved. |
| 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 |
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.
