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Bayesian Multi-View Graph Convolutional Network (BMGCN) for Integrative Multi-Omics Analysis with Survival Outcomes and Zero-Inflated Data

2025-10-27

Abstract excerpt

Modern biomedical research generates vast, multi-modal datasets (multi-omics) from the same patient cohorts, offering an unprecedented opportunity to understand complex diseases. However, integrating these heterogeneous data views to predict clinical outcomes like patient survival presents significant statistical challenges. These challenges include data heterogeneity, high dimensionality, inherent zero-inflation...

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Literature Corpus work
6731463d-77a7-50df-b2b4-316aabb9628d
DOI
10.20944/preprints202510.1979.v1
Open publication

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Bayesian Multi-View Graph Convolutional Network (BMGCN) for Integrative Multi-Omics Analysis with Survival Outcomes and Zero-Inflated DataDOI 10.20944/preprints202510.1979.v1
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