Machine Learning-Driven Prediction of Brain Age for Alzheimer’s Risk: APOE4 Genotype and Gender Effects
<b>Background:</b> Alzheimer’s disease (AD) is a leading cause of dementia, and it is significantly influenced by the apolipoprotein E4 (APOE4) gene and gender. This study aimed to use machine learning (ML) algorithms to predict brain age and assess AD risk by considering the effects of...
Saved in:
| Main Authors: | Carter Woods, Xin Xing, Subash Khanal, Ai-Ling Lin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-09-01
|
| Series: | Bioengineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2306-5354/11/9/943 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Rare APOE p.Gly4Glu: A putative disease-causing variant for early-onset Alzheimer’s disease identified by next-generation sequencing
by: Chu-Ting Wu, et al.
Published: (2025-04-01) -
Sleep quality among sample of Egyptian patients with Alzheimer’s disease: risk factors and role of genetic profiling for ACE, ACE 2 and APO E genotypes
by: Khaled Ahmed Elbeh, et al.
Published: (2025-01-01) -
Increased cerebrospinal fluid and plasma apoE glycosylation is associated with reduced levels of Alzheimer’s disease biomarkers
by: Dobrin Nedelkov, et al.
Published: (2025-07-01) -
The APOE–Microglia Axis in Alzheimer’s Disease: Functional Divergence and Therapeutic Perspectives—A Narrative Review
by: Aiwei Liu, et al.
Published: (2025-06-01) -
HDL‐Apolipoprotein in Alzheimer's Disease Revisited: From Periphery to CNS
by: Yihong Huang, et al.
Published: (2025-04-01)