Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005–2023)
Article
Article Title | Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005–2023) |
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ERA Journal ID | 5039 |
Article Category | Article |
Authors | Zamanian, H., Shalbaf, A., Zali, M.R., Khalaj, A.R., Dehghan, P., Tabesh, M., Hatami, B., Alizadehsani, R., Tan, Ru-San and Acharya, U. Rajendra |
Journal Title | Computer Methods and Programs in Biomedicine |
Journal Citation | 244 |
Article Number | 107932 |
Number of Pages | 13 |
Year | 2024 |
Publisher | Elsevier |
ISSN | 0169-2607 |
1872-7565 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.cmpb.2023.107932 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0169260723005989 |
Abstract | Background and objectives Methods Results Conclusion |
Keywords | Artificial intelligence; Deep learning ; Machine learning ; NAFLD; NASH; Fatty liver ; Diagnosis; Healthcare |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 420308. Health informatics and information systems |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Shahid Beheshti University of Medical Sciences, Iran |
Shahed University, Iran | |
Tehran University of Medical Sciences, Iran | |
Deakin University | |
National Heart Centre, Singapore | |
Duke-NUS Medical School, Singapore | |
School of Mathematics, Physics and Computing | |
Centre for Health Research |
https://research.usq.edu.au/item/z5w02/application-of-artificial-intelligence-techniques-for-non-alcoholic-fatty-liver-disease-diagnosis-a-systematic-review-2005-2023
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