Article

Advancing cardiovascular disease risk prediction beyond conventional methods: a systematic review of multimodal machine learning models integrating traditional clinical factors and multi-omics data

2025-10-08

Abstract excerpt

<h4>Background</h4> Cardiovascular disease (CVD) is a leading global health burden. Traditional risk prediction models, though widely used, often overlook genetic predisposition and other complex biological factors, which significantly impacts CVD risk. The emergence of multi-omics technologies now enables a more comprehensive view of an individual’s risk, but integrating such high-dimensional data has been chall...

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Literature Corpus work: 9a0901c2-4cf7-551a-925c-f79303160adb
DOI: 10.1101/2025.10.07.25337473

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