Integrating phenotypic information of obstructive sleep apnea and deep representation of sleep-event sequences for cardiovascular risk prediction
Models that are aware of OSA phenotypes are preferred, and lifestyle factors should be an important focus for precise CV prevention and risk management in the general and OSA populations.
Authors
- Yali Zheng (ORCID: https://orcid.org/0000-0002-6215-1694)
- Zhengbi Song
- Xiao Peng
- yu huang
- Bo Cheng
- Qing Huo Liu
- Min Min
Institutions
- Sun Yat-sen University (CN)
- Shenzhen Technology University (CN)
- Eighth Affiliated Hospital of Sun Yat-sen University
- Xi’an Jiaotong-Liverpool University (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2026-03-16
- DOI
- https://doi.org/10.1186/s12911-026-03439-8
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00