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Article

Multimodal deep learning approaches for improving polygenic risk scores with imaging data.

Scientific reports - 5 Jan 2026

Kim Hyeongmu, Lee Geon, Chung Wonil

Abstract excerpt

Enhancing the predictive accuracy of polygenic risk scores (PRS) can be achieved by incorporating imaging data, which captures disease-related phenotypic variations. This study aimed to evaluate the predictive performance of PRS, image-derived deep learning scores (IDS), imaging-derived phenotypes (IDPs), and clinical covariates. Additionally, IDP-proxy genetic scores (IGSs) were developed as substitutes for IDPs...

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Share to Deep Learning
Share to Genetic Predisposition to Disease
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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Share to Multifactorial Inheritance

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Share to Tomography, Optical Coherence

Source

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Identifiers

PMID: 41491351
DOI: 10.1038/s41598-025-34153-6
PMCID: PMC12855870

Genes

IDS

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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