The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea (2025)
- Authors:
- USP affiliated authors: ÉCKELI, ÁLAN LUIZ - FMRP ; SALGADO, HELIO CESAR - FMRP ; TINÓS, RENATO - FFCLRP ; FAZAN JÚNIOR, RUBENS - FMRP
- Unidades: FMRP; FFCLRP
- DOI: 10.3389/fcvm.2025.1389402
- Subjects: APNEIA DO SONO; FREQUÊNCIA CARDÍACA
- Keywords: Obstructive sleep apnea; Autonomic modulation of the heart; Heart rate variability; Oxygen saturation; Machine learning
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Frontiers in Cardiovascular Medicine
- ISSN: 2297-055X
- Volume/Número/Paginação/Ano: v. 12, art. 1389402, p. 1-10, 2025
- Este artigo possui versão em acesso aberto
- URL de acesso aberto
- PDF de acesso aberto
- Versão do Documento: Versão publicada (Published version)
-
Status: Artigo publicado em periódico de acesso aberto (Gold Open Access) -
ABNT
SANTOS, Rafael Rodrigues dos et al. The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea. Frontiers in Cardiovascular Medicine, v. 12, p. 1-10, 2025Tradução . . Disponível em: https://doi.org/10.3389/fcvm.2025.1389402. Acesso em: 15 mar. 2026. -
APA
Santos, R. R. dos, Marumo, M. B., Eckeli, A. L., Salgado, H. C., Silva, L. E. V. da, Tinós, R., & Fazan Júnior, R. (2025). The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea. Frontiers in Cardiovascular Medicine, 12, 1-10. doi:10.3389/fcvm.2025.1389402 -
NLM
Santos RR dos, Marumo MB, Eckeli AL, Salgado HC, Silva LEV da, Tinós R, Fazan Júnior R. The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea [Internet]. Frontiers in Cardiovascular Medicine. 2025 ; 12 1-10.[citado 2026 mar. 15 ] Available from: https://doi.org/10.3389/fcvm.2025.1389402 -
Vancouver
Santos RR dos, Marumo MB, Eckeli AL, Salgado HC, Silva LEV da, Tinós R, Fazan Júnior R. The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea [Internet]. Frontiers in Cardiovascular Medicine. 2025 ; 12 1-10.[citado 2026 mar. 15 ] Available from: https://doi.org/10.3389/fcvm.2025.1389402 - Heart rate variability and oximetry indices to detect obstructive sleep apnea using machine learning algorithms
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