| 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 |
Minireviews |
| Article Title |
Artificial intelligence for hepatitis evaluation
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Wei Liu, Xue Liu, Mei Peng, Gong-Quan Chen, Peng-Hua Liu, Xin-Wu Cui, Fan Jiang and Christoph F Dietrich |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Natural Science Foundation of China |
82071953 |
| Department of Science and Technology of Hunan Province |
2020SK52103 |
|
| Corresponding Author |
Xin-Wu Cui, MD, PhD, Professor, Sino-German Tongji-Caritas Research Center of Ultrasound in Medicine, Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Avenue , Wuhan 430030, Hubei , China. cuixinwu@live.cn |
| Key Words |
Machine learning; Deep learning; Radiomics; Hepatitis; Fibrosis; Hepatocellular carcinoma |
| Core Tip |
Currently, there is a need of a comprehensive review to introduce the applications of artificial intelligence (AI) in hepatitis. We firstly discuss the possible value of AI based data mining in predicting the incidence of hepatitis, classifying the different stages of hepatitis, diagnosing or screening for hepatitis, forecasting the progression of hepatitis, and predicting response to antiviral drugs in chronic hepatitis C patients. In addition, we introduce the applications of AI based on radiology in predicting hepatitis and liver fibrosis, grading hepatocellular carcinoma (HCC) and differentiating from benign liver tumors, predicting the risk of vascular invasion of HCC, the risk of hepatic encephalopathy secondary to hepatitis B related cirrhosis. |
| Publish Date |
2021-09-09 06:46 |
| Citation |
Liu W, Liu X, Peng M, Chen GQ, Liu PH, Cui XW, Jiang F, Dietrich CF. Artificial intelligence for hepatitis evaluation. World J Gastroenterol 2021; 27(34): 5715-5726 |
| URL |
https://www.wjgnet.com/1007-9327/full/v27/i34/5715.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v27.i34.5715 |
