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Articles Published Processes
9/18/2025 9:55:59 AM | Browse: 402 | Download: 55
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Received |
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2025-05-21 04:08 |
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Peer-Review Started |
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2025-05-21 09:14 |
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To Make the First Decision |
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Return for Revision |
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2025-06-07 06:14 |
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Revised |
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2025-06-19 16:51 |
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Second Decision |
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2025-09-01 02:37 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-09-01 05:21 |
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Articles in Press |
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2025-09-01 05:21 |
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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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2025-09-08 07:13 |
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Publish the Manuscript Online |
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2025-09-18 09:55 |
| 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) 2025. 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 |
Letter to the Editor |
| Article Title |
Machine learning as an artificial intelligence application in management of chronic hepatitis B virus infection
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Wafaa Mohamed Ezzat |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Wafaa Mohamed Ezzat, Department of Internal Medicine, Medical Research and Clinical Studies Institute, National Research Center, El Buhoth Street, Cairo, Giza 12311, Egypt. wafaa_3t@yahoo.com |
| Key Words |
Artificial intelligence; Machine learning; Gut microbiota; Hepatitis B virus; Infection |
| Core Tip |
There is substantial evidence indicating that stratification based on the gut microbiome could facilitate personalized interventions aimed at enhancing human health. It became essential to characterize the microbial ecosystems, resulting in a surge of various types of molecular profiling data, including metagenomics, metatranscriptomics, and metabolomics. In the analysis of such data, machine learning algorithms have proven to be effective in identifying crucial molecular signatures, uncovering potential patient stratifications, and especially in creating models that can reliably predict phenotypes. Machine learning may be supervised, unsupervised, semi-supervised or reinforcement type. Using a method for explaining individual classifier decisions for complex microbiota analysis may help in developing personalized treatment. |
| Publish Date |
2025-09-18 09:55 |
| Citation |
<p>Ezzat WM. Machine learning as an artificial intelligence application in management of chronic hepatitis B virus infection. <i>World J Gastroenterol</i> 2025; 31(35): 109776</p> |
| URL |
https://www.wjgnet.com/1007-9327/full/v31/i35/109776.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v31.i35.109776 |
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