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Articles Published Processes
3/26/2026 9:22:55 AM | Browse: 0 | Download: 0
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Received |
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2025-11-06 07:01 |
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Peer-Review Started |
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2025-11-06 07:01 |
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First Decision by Editorial Office Director |
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2025-11-14 06:46 |
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Return for Revision |
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2025-11-14 06:46 |
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Revised |
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2025-11-23 15:39 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-01-07 02:41 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-01-07 09:38 |
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Articles in Press |
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2026-01-07 09:38 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-03-16 00:51 |
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Publish the Manuscript Online |
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2026-03-26 09:22 |
| ISSN |
1948-5182 (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) 2026. Published by Baishideng Publishing Group Inc. All rights reserved. |
| 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 |
Minireviews |
| Article Title |
Advances in artificial intelligence for imaging-based diagnosis of hepatocellular carcinoma
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Zi-Xiong Zhou, Jia-Jia Xiao and Zhong-Xing Ning |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| School Level Project of Guangxi Vocational and Technical College |
231208 |
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| Corresponding Author |
Zhong-Xing Ning, Department of Hypertension and Vascular Disease, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan 2nd Road, Yuexiu District, Guangzhou 510080, Guangdong Province, China. 592220690@qq.com |
| Key Words |
Hepatocellular carcinoma; Imaging-guided diagnosis; Artificial intelligence; Deep learning; Clinical translation |
| Core Tip |
Artificial intelligence (AI) for image-guided hepatocellular carcinoma diagnosis improves sensitivity to small lesions, enables standardized quantitative readouts, and reduces reporting time, thereby complementing conventional radiology. Built on diverse imaging datasets and evolving model designs, AI has advanced across detection, segmentation, characterization, and response assessment, with early clinical uptake. Outstanding obstacles-cross-institution generalization and clinically meaningful explainability-must be resolved to achieve scalable, trustworthy deployment. |
| Publish Date |
2026-03-26 09:22 |
| Citation |
Zhou ZX, Xiao JJ, Ning ZX. Advances in artificial intelligence for imaging-based diagnosis of hepatocellular carcinoma. World J Hepatol 2026; 18(3): 116233 |
| URL |
https://www.wjgnet.com/1948-5182/full/v18/i3/116233.htm |
| DOI |
https://dx.doi.org/10.4254/wjh.v18.i3.116233 |
© 1993-2026 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
California Corporate Number: 3537345
