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A Bioinformatic Analysis for Identifying Key Genes in Atrial Fibrillation

Year: 2025

Type: conference-paper

Abstract: Background: The most frequently occurring form of sustained cardiac arrhythmia is atrial fibrillation (AF). Research consistently shows that genetic alterations significantly influence the development and progression of AF. This study explored bioinformatic analysis and machine learning to identify key genes linked to AF.

DOI: 10.1145/3747357.3747368

Authors: Bin Deng, Angxin Song, Junguo Zhang, Xiangna Yang, Yingyi Yu

Institutions: Guizhou University, Sun Yat-sen University, Guangzhou Women and Children Medical Center, Guangzhou Medical University, Guizhou University of Commerce

Language: English

Topic: Atrial Fibrillation Management and Outcomes

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Funder: Department of Education of Guizhou Province

OpenAlex ID: W4413578022

FWCI:

Cites: 31

Cited by:

Related to: 10