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. 77131 - 77141. ISSN 2169-3536. (Published)
![[img]](http://umpir.ump.edu.my/style/images/fileicons/other.png) |
Pdf
09075205.pdf Restricted to Repository staff only Download (1MB) | Request a copy |
|
|
Pdf
Alzheimer's diseases detection by using deep learning algorithms.pdf Download (199kB) | Preview |
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 |
|---|---|
| Additional Information: | Indexed by Scopus & WOS |
| Uncontrolled Keywords: | Alzheimer’s disease; Deep learning; Early stage detection and diagnosis |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Faculty of Computing |
| Depositing User: | Dr. Taha Hussein Alaaldeen Rassem |
| Date Deposited: | 14 Jul 2020 02:10 |
| Last Modified: | 14 Jul 2020 02:10 |
| URI: | http://umpir.ump.edu.my/id/eprint/28454 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |