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Recursive Support Vector Machine Biomarker Selection for Alzheimer’s Disease

18 Jan 2021

Abstract excerpt

BACKGROUND: There is a need for more reliable diagnostic tools for the early detection of Alzheimer's disease (AD). This can be a challenge due to a number of factors and logistics making machine learning a viable option. OBJECTIVE: In this paper, we present on a Support Vector Machine Leave-One-Out Recursive Feature Elimination and Cross Validation (SVM-RFE-LOO) algorithm for use in the early detection of AD and...

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Share to Advanced Proteomics Techniques and Applications
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PMID: 33492292
DOI: 10.3233/jad-201254

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