Applying machine learning to high-dimensional proteomics datasets for the identification of Alzheimer’s disease biomarkers

Applying machine learning to high-dimensional proteomics datasets for the identification of Alzheimer’s disease biomarkers

Abstract Purpose This study explores the application of machine learning to high-dimensional proteomics datasets for identifying Alzheimer’s disease (AD) biomarkers. AD, a neurodegenerative disorder affecting millions worldwide, necessitates early and accurate diagnosis for effective management. Met...

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Bibliographic Details
Main Authors: Christoffer Ivarsson Orrelid, Oscar Rosberg, Sophia Weiner, Fredrik D. Johansson, Johan Gobom, Henrik Zetterberg, Newton Mwai, Lena Stempfle
Format: Article
Language:English
Published: BMC 2025-03-01
Series:Fluids and Barriers of the CNS
Subjects:
Alzheimer’s disease
Proteomics
Mass spectrometry
High-dimensional data
Biomarkers
Machine learning
Online Access:https://doi.org/10.1186/s12987-025-00634-z
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https://doi.org/10.1186/s12987-025-00634-z

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