Screening for moderate to severe obstructive sleep apnea by using heart rate variability features based on random forest algorithm
The RF prediction model can effectively distinguish patients with moderate to severe OSA, which is expected to carry out in a large-scale population in order to screening for high-risk patients, and helps to evaluate the effect of OSA treatment continuously.
Authors
- Chenxu Zhang (ORCID: https://orcid.org/0009-0001-7017-7739)
- Ping Zeng (ORCID: https://orcid.org/0000-0002-4022-2551)
- Xiaoqing Zhang (ORCID: https://orcid.org/0009-0007-8071-137X)
- Liang Yu (ORCID: https://orcid.org/0009-0007-3922-3454)
- Lin Li (ORCID: https://orcid.org/0009-0004-8777-6983)
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
Publication Details
- Journal
- Sleep And Breathing
- Published
- 2024-09-10
- DOI
- https://doi.org/10.1007/s11325-024-03151-9
- Citations
- 3
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 0.98
Funders
- Department of Science and Technology of Sichuan Province