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) |
|---|---|
| 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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