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Articles Published Processes
5/27/2021 9:41:33 AM | Browse: 455 | Download: 1529
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Received |
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2021-02-13 14:55 |
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Peer-Review Started |
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2021-02-13 14:57 |
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To Make the First Decision |
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Return for Revision |
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2021-03-14 02:55 |
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Revised |
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2021-04-01 18:27 |
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Second Decision |
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2021-04-15 12:02 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2021-04-21 13:54 |
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Articles in Press |
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2021-04-21 13:54 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2021-05-05 11:01 |
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Typeset the Manuscript |
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2021-05-25 10:24 |
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Publish the Manuscript Online |
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2021-05-27 09:41 |
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: http://creativecommons.org/Licenses/by-nc/4.0/ |
Copyright |
© The Author(s) 2021. 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 |
Observational Study |
Article Title |
Prediction of hepatic inflammation in chronic hepatitis B patients with a random forest-backward feature elimination-algorithm
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Manuscript Source |
Invited Manuscript |
All Author List |
Ji-Yuan Zhou, Liu-Wei Song, Rong Yuan, Xiao-Ping Lu and Gui-Qiang Wang |
ORCID |
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Funding Agency and Grant Number |
Funding Agency |
Grant Number |
China Mega-Project for Infectious Diseases |
2017ZX10203202 |
Guangdong Basic and Applied Basic Research Foundation |
2019A1515110060 |
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Corresponding Author |
Gui-Qiang Wang, MD, Chairman, Director, Director, Professor, Department of Infectious Disease, Peking University First Hospital, No. 8 Xishiku Street, Xicheng District, Beijing 100034, China. john131212@126.com |
Key Words |
Hepatic inflammation; Machine learning; Quantitative hepatitis B core antibody; CXCL11; Diagnostic efficiency |
Core Tip |
We aimed to propose an effective backward feature elimination algorithm utilizing random forest to select optimal features and construct a novel non-invasive model for predicting hepatitis B-related hepatic inflammation based on a large, multicenter cohort. The results indicated that the I-3A index constructed based on the selected features significantly improved the diagnostic efficiency of quantitative hepatitis B core antibody alone for predicting moderate-to-severe inflammation. Additionally, the I-3A index showed high diagnostic accuracy for moderate-to-severe inflammation in both HBeAg-positive and HBeAg-negative chronic hepatitis B patients. |
Publish Date |
2021-05-27 09:41 |
Citation |
Zhou JY, Song LW, Yuan R, Lu XP, Wang GQ. Prediction of hepatic inflammation in chronic hepatitis B patients with a random forest-backward feature elimination-algorithm. World J Gastroenterol 2021; 27(21): 2910-2920 |
URL |
https://www.wjgnet.com/1007-9327/full/v27/i21/2910.htm |
DOI |
https://dx.doi.org/10.3748/wjg.v27.i21.2910 |
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