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Articles Published Processes
9/7/2023 1:29:18 AM | Browse: 177 | Download: 607
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Received |
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2023-06-04 13:25 |
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Peer-Review Started |
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2023-06-04 13:27 |
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To Make the First Decision |
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Return for Revision |
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2023-07-28 08:48 |
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Revised |
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2023-08-18 15:52 |
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Second Decision |
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2023-09-05 02:51 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2023-09-05 07:35 |
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Articles in Press |
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2023-09-05 07:35 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2023-08-31 10:26 |
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Typeset the Manuscript |
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2023-09-05 08:48 |
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Publish the Manuscript Online |
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2023-09-07 01:29 |
ISSN |
2644-3236 (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) 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 |
Observational Study |
Article Title |
Drug-induced liver injury and COVID-19: Use of artificial intelligence and the updated Roussel Uclaf Causality Assessment Method in clinical practice
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Manuscript Source |
Unsolicited Manuscript |
All Author List |
Gabriela Xavier Ortiz, Ana Helena Dias Pereira dos Santos Ulbrich, Gabriele Lenhart, Henrique Dias Pereira dos Santos, Karin Hepp Schwambach, Matheus William Becker and Carine Raquel Blatt |
ORCID |
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Funding Agency and Grant Number |
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Corresponding Author |
Gabriela Xavier Ortiz, MSc, Academic Research, Graduate Program in Medicine – Hepatology, Federal University of Health Sciences of Porto Alegre, Sarmento Leite, 245, Porto Alegre 90050-170, Brazil. gabrielax@ufcspa.edu.br |
Key Words |
Chemical and drug induced liver injury; RUCAM; Artificial intelligence; COVID-19; Liver injury |
Core Tip |
This is a real-life study that correlated hospital clinical pharmacy data with artificial intelligence (AI) and pharmacovigilance in coronavirus disease 2019 (COVID-19) inpatients. Inpatient screening for liver injury was made with AI and drug-induced liver injury was evaluated with the Roussel Uclaf Causality Assessment Method (RUCAM) algorithm. A total of 17 COVID-19 inpatients were evaluated, there were 31 suspected drugs, RUCAM score: possible (n = 24), probable (n = 5), and unlikely (n = 2). This study contributed to the patient safety and pharmacovigilance database. These results are included in a project of clinical pharmacy using AI tools. |
Publish Date |
2023-09-07 01:29 |
Citation |
Ortiz GX, Ulbrich AHDPS, Lenhart G, dos Santos HDP, Schwambach KH, Becker MW, Blatt CR. Drug-induced liver injury and COVID-19: Use of artificial intelligence and the updated Roussel Uclaf Causality Assessment Method in clinical practice. Artif Intell Gastroenterol 2023; 4(2): 36-47 |
URL |
https://www.wjgnet.com/2644-3236/full/v4/i2/36.htm |
DOI |
https://dx.doi.org/10.35712/aig.v4.i2.36 |
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