Article

Uncovering genetic architecture of the heart via genetic association studies of unsupervised deep learning derived endophenotypes

2025-09-20

Abstract excerpt

Recent genome-wide association studies (GWAS) have effectively linked genetic variants to quantitative traits derived from time-series cardiac magnetic resonance imaging, revealing insights into cardiac morphology and function. Deep learning approach generally requires extensive supervised training on manually annotated data. In this study, we developed a novel framework using a 3D U-architecture autoencoder (cine...

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Literature Corpus work: 4587245a-7551-51a0-91ee-01ef4a10acf2
DOI: 10.1101/2025.09.17.676827

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