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Article

Genome-wide association study-based prediction of atrial fibrillation using artificial intelligence.

Open heart - 1 Jan 2022

Kwon Oh-Seok, Hong Myunghee, Kim Tae-Hoon, Hwang Inseok, Shim Jaemin, Choi Eue-Keun, Lim Hong Euy, Yu Hee Tae, Uhm Jae-Sun, Joung Boyoung, Oh Seil, Lee Moon-Hyoung, Kim Young-Hoon, Pak Hui-Nam

Abstract excerpt

OBJECTIVE: We previously reported early-onset atrial fibrillation (AF) associated genetic loci among a Korean population. We explored whether the AF-associated single-nucleotide polymorphisms (SNPs) selected from the Genome-Wide Association Study (GWAS) of an external large cohort has a prediction power for AF in Korean population through a convolutional neural network (CNN). METHODS: This study included 6358...

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Identifiers

PMID: 35086918
DOI: 10.1136/openhrt-2021-001898
PMCID: PMC8796259

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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