Identification of Plasma Proteins Associated with Alzheimer's Disease Using Feature Selection Techniques and Machine Learning Algorithms
Alzheimer’s disease (AD) is a chronic, progressive neurodegenerative disorder that typically affects elderly individuals. Detecting Alzheimer’s using plasma proteins is a critical step toward improving treatment results for this disease. This study aims to use computational algorithms to explore th...
Saved in:
| Main Authors: | Zakaria Mokadem, Mohamed Djerioui, Bilal Attallah, Youcef Brik |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IMS Vogosca
2025-02-01
|
| Series: | Science, Engineering and Technology |
| Subjects: | |
| Online Access: | https://www.setjournal.com/SET/article/view/189 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Comparison of Machine Learning Algorithms for Predicting Alzheimer’s Disease Using Neuropsychological Data
by: Zakaria Mokadem, et al.
Published: (2024-12-01) -
Prospective evaluation of plasma pTau217 stability for the detection of Alzheimer’s disease in a tertiary memory clinic
by: Javier Arranz, et al.
Published: (2025-07-01) -
Accurate and robust prediction of Amyloid-β brain deposition from plasma biomarkers and clinical information using machine learning
by: Jiayuan Xu, et al.
Published: (2025-08-01) -
Plasma phospho-tau217 as a predictive biomarker for Alzheimer’s disease in a large south American cohort
by: Neetesh Pandey, et al.
Published: (2025-01-01) -
Cerebrospinal fluid and plasma biomarker trajectories with increasing amyloid deposition in Alzheimer's disease
by: Sebastian Palmqvist, et al.
Published: (2019-11-01)