Mazo, Claudia et al.
ORCID: 0000-0003-1703-8964
(2025)
Machine learning applications in vascular neuroimaging for the diagnosis and prognosis of cognitive impairment and dementia:
a systematic review and meta-analysis.
Alzheimer's Research & Therapy, 17
(183).
ISSN 1758-9193
Abstract
Cerebral small vessel disease (CSVD) is a common neurological condition that contributes to strokes, dementia, disability, and mortality worldwide. We conducted a systematic review and meta-analysis to investigate the
use of neuroimaging CSVD markers in machine learning (ML) based diagnosis and prognosis of cognitive impairment and dementia, and identify both methodological changes over time and barriers to clinical translation
Metadata
| Item Type: | Article (Published) |
|---|---|
| Refereed: | Yes |
| Uncontrolled Keywords: | Machine learning, Dementia, Cerebral small vessel disease, Artificial intelligence, Neuroimaging, Cognitive impairment, Alzheimer’s dementia, Neurodegenerative diseases |
| Subjects: | Computer Science > Computer engineering Computer Science > Computer networks |
| DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing |
| Publisher: | BioMed Central Ltd. |
| Official URL: | https://alzres.biomedcentral.com/articles/10.1186/... |
| Copyright Information: | Authors |
| ID Code: | 31505 |
| Deposited On: | 05 Sep 2025 10:12 by Gordon Kennedy . Last Modified 05 Sep 2025 10:12 |
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