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Article

Integrating phenotypic information of obstructive sleep apnea and deep representation of sleep-event sequences for cardiovascular risk prediction.

BMC medical informatics and decision making - 16 Mar 2026

Zheng Yali, Song Zhengbi, Cheng Bo, Peng Xiao, Huang Yu, Liu Qing, Min Min

Abstract excerpt

BACKGROUND: Advances in wearable and machine learning technologies have opened new possibilities for predicting cardiovascular (CV) risk. Moreover, the association between obstructive sleep apnea (OSA) and CV risk has been well recognized. However, how to integrate such information effectively to enhance risk prediction remains unclear. This study seeks to explore effective strategies for incorporating OSA...

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Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

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Identifiers

PMID: 41840572
DOI: 10.1186/s12911-026-03439-8
PMCID: PMC13104391

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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