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Articles Published Processes
4/29/2022 11:12:04 AM | Browse: 517 | Download: 856
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Received |
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2021-12-31 01:26 |
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Peer-Review Started |
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2021-12-31 01:27 |
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To Make the First Decision |
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Return for Revision |
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2022-02-07 03:11 |
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Revised |
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2022-02-18 18:19 |
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Second Decision |
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2022-04-28 03:28 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2022-04-28 04:17 |
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Articles in Press |
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2022-04-28 04:17 |
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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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2022-04-28 11:10 |
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Publish the Manuscript Online |
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2022-04-29 11:12 |
| 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) 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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Minireviews |
| Article Title |
Application of artificial intelligence in non-alcoholic fatty liver disease and viral hepatitis
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Atchayaa Gunasekharan, Joanna Jiang, Ashley Nickerson, Sajid Jalil and Khalid Mumtaz |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Khalid Mumtaz, MBBS, MSc, Associate Professor, Medicine, Ohio State University, 395 W. 12th Avenue, Columbus, Ohio 43210, United States. khalid.mumtaz@osumc.edu |
| Key Words |
Non-alcoholic fatty liver disease; Non-alcoholic steatohepatitis; Fatty liver; Artificial intelligences; Steatosis; Fibrosis; Machine learning |
| Core Tip |
Non-alcoholic fatty liver disease (NAFLD) exists on a spectrum from simple hepatocyte steatosis to non-alcoholic steatohepatitis (NASH) with ballooning and fibrosis. Given the lack of efficient screening methods and high rate of asymptomatic disease, it is challenging to identify patients with NAFLD in its various stages. Although liver biopsy remains the gold standard for diagnosing NASH, it is an invasive, costly, and painful procedure. Conventional imaging modalities including ultrasound, computed tomography, magnetic resonance imaging and transient elastography are limited by inter- and intra-observer variability depending on the stage of fibrosis. Similarly, despite recent progress in the prevention and treatment of viral hepatitis, predicting sustained virological response and disease progression remains challenging. Artificial intelligence (AI) is an exciting and increasingly pertinent field in medicine as clinicians incorporate augmenting technology into their daily practice. This review summarizes recent literature on the application of AI in NAFLD and viral hepatitis. Specifically, the review will assess the performance of AI as a non-invasive method for the diagnosis and staging of liver fibrosis and steatosis, as well as for the detection and treatment of chronic viral hepatitis. It will also aim to highlight the potential for AI based methods on their ability to develop therapeutic targets. |
| Publish Date |
2022-04-29 11:12 |
| Citation |
Gunasekharan A, Jiang J, Nickerson A, Jalil S, Mumtaz K. Application of artificial intelligence in non-alcoholic fatty liver disease and viral hepatitis. Artif Intell Gastroenterol 2022; 3(2): 46-53 |
| URL |
https://www.wjgnet.com/2644-3236/full/v3/i2/46.htm |
| DOI |
https://dx.doi.org/10.35712/aig.v3.i2.46 |
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