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Articles Published Processes
11/25/2022 2:19:16 AM | Browse: 677 | Download: 1644
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Received |
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2022-09-11 20:24 |
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Peer-Review Started |
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2022-09-11 20:28 |
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First Decision by Editorial Office Director |
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2022-09-29 21:11 |
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Return for Revision |
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2022-09-29 21:11 |
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Revised |
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2022-10-07 16:32 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2022-11-11 03:14 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2022-11-17 15:03 |
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Articles in Press |
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2022-11-17 15:03 |
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Edit the Manuscript by Language Editor |
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2022-11-08 16:35 |
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Typeset the Manuscript |
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2022-11-18 09:28 |
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Publish the Manuscript Online |
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2022-11-25 02:19 |
| 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) 2022. 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 |
Endocrinology & Metabolism |
| Manuscript Type |
Review |
| Article Title |
Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases
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| Manuscript Source |
Invited Manuscript |
| All Author List |
J Alfredo Martínez, Marta Alonso-Bernáldez, Diego Martínez-Urbistondo, Juan A Vargas-Nuñez, Ana Ramírez de Molina, Alberto Dávalos and Omar Ramos-Lopez |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| European Regional Development Fund |
(ERDF)-REACT-EU |
| Synergic R&D Projects |
METAINFLAMATION-Y2020/BIO-6600 |
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| Corresponding Author |
Omar Ramos-Lopez, PhD, Professor, Medicine and Psychology School, Autonomous University of Baja California, Universidad 14418, UABC, Parque Internacional Industrial, Tijuana 22390, Baja California, Mexico. oscar.omar.ramos.lopez@uabc.edu.mx |
| Key Words |
Machine learning; Liver inflammation; Liver disease; Viral diseases; Comorbidity |
| Core Tip |
Chronic liver disease has become a global burden, and new approaches need to be explored to tackle this disease. In this context, machine learning techniques bring a whole new set of opportunities to study novel approaches and biomarkers for prevention, diagnosis, treatment, and prognosis of inflammatory and virus-related liver diseases. The application of machine learning algorithms constitutes a pivotal piece of personalized medicine, allowing the integration of different phenotypical and genotypical data for a precision outcome concerning inflammatory liver comorbidities in non-communicable and viral diseases. |
| Publish Date |
2022-11-25 02:19 |
| Citation |
Martínez JA, Alonso-Bernáldez M, Martínez-Urbistondo D, Vargas-Nuñez JA, Ramírez de Molina A, Dávalos A, Ramos-Lopez O. Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases. World J Gastroenterol 2022; 28(44): 6230-6248 |
| URL |
https://www.wjgnet.com/1007-9327/full/v28/i44/6230.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v28.i44.6230 |
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