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Analysis of Potential Genetic Biomarkers Using Machine Learning Methods and Immune Infiltration Regulatory Mechanisms Underlying Atrial Fibrillation Running Title: Identification of Biomarkers for Af via Machine Learning

2021-12-29

Abstract excerpt

<h4>Objective: </h4> We aimed to screen out biomarkers for atrial fibrillation (AF) based on machine learning methods and evaluate the degree of immune infiltration in AF patients in detail. <h4>Methods: </h4>: Two datasets (GSE41177 and GSE79768) related to AF in GEO database were included. Differentially expressed genes (DEGs) were screened out using “limma” package. Candidate biomarkers for AF were identified u...

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Literature Corpus work
d05abd89-8f5b-551c-be5b-bf59badc1988
DOI
10.21203/rs.3.rs-1136927/v1
Open publication

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Analysis of Potential Genetic Biomarkers Using Machine Learning Methods and Immune Infiltration Regulatory Mechanisms Underlying Atrial Fibrillation Running Title: Identification of Biomarkers for Af via Machine LearningDOI 10.21203/rs.3.rs-1136927/v1
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