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Articles Published Processes
3/12/2024 10:04:17 AM | Browse: 58 | Download: 74
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Received |
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2023-10-30 02:37 |
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Peer-Review Started |
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2023-10-30 02:39 |
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To Make the First Decision |
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Return for Revision |
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2023-12-22 15:09 |
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Revised |
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2023-12-26 13:01 |
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Second Decision |
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2024-01-29 02:06 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2024-01-29 05:48 |
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Articles in Press |
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2024-01-29 05:48 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2024-02-28 01:02 |
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Publish the Manuscript Online |
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2024-03-12 10:04 |
| 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 |
© The Author(s) 2024. 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 |
Retrospective Study |
| Article Title |
Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma: Machine learning model based on contrast-enhanced computed tomography
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Chao Zhang, Hai Zhong, Fang Zhao, Zhen-Yu Ma, Zheng-Jun Dai and Guo-Dong Pang |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Guo-Dong Pang, MD, PhD, Associate Chief Physician, Doctor, Department of Radiology, The Second Hospital of Shandong University, No. 247 Beiyuan Road, Tianqiao District, Jinan 250033, Shandong Province, China. pgd226@aliyun.com |
| Key Words |
Hepatocellular carcinoma; Vessels encapsulating tumor clusters; Intratumoral and peritumoral regions; Radiomics features; Nomogram |
| Core Tip |
Vessels encapsulating tumor clusters (VETC) is an independent risk factor for poor prognosis in hepatocellular carcinoma (HCC) and currently determined only on histologic examination after surgical resection. We evaluated 190 patients with pathologically confirmed HCC and constructed a machine learning-based contrast-enhanced computed tomography radiomics model, performed canonical screening of features and multiple validations, and confirmed robustness on various data resources. The radiomics model showed remarkable performance in predicting the VETC subtype, and the results were reproducible, demonstrating that the approach may be applied to other patient samples. Radiomics could provide valuable information for assisting clinicians in pretreatment decision-making. |
| Publish Date |
2024-03-12 10:04 |
| Citation |
Zhang C, Zhong H, Zhao F, Ma ZY, Dai ZJ, Pang GD. Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma: Machine learning model based on contrast-enhanced computed tomography. World J Gastrointest Oncol 2024; 16(3): 857-874 |
| URL |
https://www.wjgnet.com/1948-5204/full/v16/i3/857.htm |
| DOI |
https://dx.doi.org/10.4251/wjgo.v16.i3.857 |
© 2004-2024 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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