Al-Shoukry, Suhad and Rassem, Taha H. and Makbol, Nasrin M. (2020) Alzheimer’s diseases detection by using deep learning algorithms: A mini-review. IEEE Access, 8 (9075205). 77131 -77141. ISSN 2169-3536. (Published)
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Abstract
The accurate diagnosis of Alzheimer's disease (AD) plays an important role in patient treatment, especially at the disease's early stages, because risk awareness allows the patients to undergo preventive measures even before the occurrence of irreversible brain damage. Although many recent studies have used computers to diagnose AD, most machine detection methods are limited by congenital observations. AD can be diagnosed-but not predicted-at its early stages, as prediction is only applicable before the disease manifests itself. Deep Learning (DL) has become a common technique for the early diagnosis of AD. Here, we briefly review some of the important literature on AD and explore how DL can help researchers diagnose the disease at its early stages.
| Item Type: | Article |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Alzheimer's disease; Deep learning; Early stage detection and diagnosis |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Computing |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 10 Nov 2023 01:00 |
| Last Modified: | 10 Nov 2023 01:00 |
| URI: | http://umpir.ump.edu.my/id/eprint/39265 |
| Download Statistic: | View Download Statistics |
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