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11/20/2023 10:41:33 AM | Browse: 108 | Download: 240
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Received |
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2023-08-26 12:57 |
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Peer-Review Started |
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2023-08-26 12:58 |
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To Make the First Decision |
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Return for Revision |
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2023-09-18 21:32 |
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Revised |
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2023-10-07 11:50 |
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Second Decision |
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2023-10-31 02:50 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2023-11-03 08:06 |
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Articles in Press |
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2023-11-03 08:06 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2023-10-30 05:03 |
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Typeset the Manuscript |
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2023-11-11 13:17 |
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Publish the Manuscript Online |
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2023-11-20 06:17 |
| ISSN |
1007-9327 (print) and 2219-2840 (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) 2023. 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 |
Development of a machine learning-based model for predicting risk of early postoperative recurrence of hepatocellular carcinoma
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Yu-Bo Zhang, Gang Yang, Yang Bu, Peng Lei, Wei Zhang and Dan-Yang Zhang |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Ningxia Key Research and Development Program |
2018BEG03001 |
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| Corresponding Author |
Peng Lei, MD, Doctor, Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, No. 84 Shenli nan Road, Yinchuan 750003, Ningxia Hui Autonomous Region, China. leipengnx@126.com |
| Key Words |
Machine learning; Hepatocellular carcinoma; Early recurrence; Risk prediction models; Imaging features; Clinical features |
| Core Tip |
The current study aimed at employing machine learning techniques to select imaging and pre-operative clinical characteristic variables, to which the clinicians were easily accessible, to develop six different risk prediction models for early postoperative recurrence of hepatocellular carcinoma (HCC). We compared the sensitivity and specificity of these models in detecting patients at high risk of early postoperative recurrence of HCC. In addition, to increase the feasibility and applicability of the constructed model, we generated a calculator online based on the predictive model to help clinicians apply it in their daily medical practice. |
| Publish Date |
2023-11-20 06:17 |
| Citation |
Zhang YB, Yang G, Bu Y, Lei P, Zhang W, Zhang DY. Development of a machine learning-based model for predicting risk of early postoperative recurrence of hepatocellular carcinoma. World J Gastroenterol 2023; 29(43): 5804-5817 |
| URL |
https://www.wjgnet.com/1007-9327/full/v29/i43/5804.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v29.i43.5804 |
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