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Articles Published Processes
7/24/2026 7:32:04 AM | Browse: 3 | Download: 0
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Received |
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2026-03-23 01:56 |
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Peer-Review Started |
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2026-03-23 01:56 |
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First Decision by Editorial Office Director |
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2026-04-03 06:41 |
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Return for Revision |
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2026-04-03 09:35 |
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Revised |
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2026-04-16 06:43 |
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Publication Fee Transferred |
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2026-04-23 06:15 |
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Second Decision by Editor |
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2026-06-08 02:40 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-06-08 09:56 |
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Articles in Press |
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2026-06-08 09:56 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-06-27 10:05 |
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Publish the Manuscript Online |
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2026-07-24 07:32 |
| ISSN |
1949-8470 (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 |
©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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Retrospective Study |
| Article Title |
Computed tomography radiomics-based machine learning nomogram for preoperative prediction of glypican-3 expression in hepatocellular carcinoma
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Zi-Han Zheng, Chun-Hua Wu, Jin-Bo Hu, Jun-Feng Xu, Xin-Yue Zi, Jin-Hui Chen, Qin He and Wen-Ying Dong |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| the Key Research and Development Program in the Field of Biomedicine of the Dali Science and Technology Bureau |
No. 20252903B030003 |
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| Corresponding Author |
Wen-Ying Dong, Director, Internal Medicine Teaching and Research, College of Nursing of Dali University, No. 22 Wanhua Road, Dali 671003, Yunnan Province, China. 157273210@qq.com |
| Key Words |
Hepatocellular carcinoma; Glypican-3; Radiomics; Machine learning; Nomogram |
| Core Tip |
Glypican-3 is a clinically relevant biomarker in hepatocellular carcinoma, but its expression is usually confirmed only after biopsy or surgical resection. This study developed a computed tomography radiomics-based machine learning nomogram for the preoperative, noninvasive prediction of glypican-3 expression. The combined model integrated a random forest-derived radiomics signature with alpha-fetoprotein and total bilirubin and showed strong predictive performance, with evidence of clinical utility. This imaging-based approach may support preoperative risk stratification and individualized management in patients with hepatocellular carcinoma. |
| Publish Date |
2026-07-24 07:32 |
| Citation |
Zheng ZH, Wu CH, Hu JB, Xu JF, Zi XY, Chen JH, He Q, Dong WY. Computed tomography radiomics-based machine learning nomogram for preoperative prediction of glypican-3 expression in hepatocellular carcinoma. World J Radiol 2026; 18(7): 121161
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| URL |
https://www.wjgnet.com/1949-8470/full/v18/i7/121161.htm |
| DOI |
https://doi.org/10.4329/wjr.121161 |
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