Pulse wave-driven machine learning for the non-invasive assessment of coronary artery calcification in patients with end-stage renal disease undergoing hemodialysis
Radial artery pulse wave analysis may serve as a non-invasive adjunct for assessing CAC severity in patients with ESRD undergoing hemodialysis.
Authors
- Z. Li (ORCID: https://orcid.org/0009-0001-4379-7270)
- Hongyang Zhao (ORCID: https://orcid.org/0000-0003-3531-2955)
- Dongmei Hao (ORCID: https://orcid.org/0000-0002-5715-5930)
- Min Ji (ORCID: https://orcid.org/0000-0002-3063-7833)
- Xinyu Zhang (ORCID: https://orcid.org/0009-0002-7331-3588)
- Ying Li (ORCID: https://orcid.org/0000-0002-3506-1255)
- Chong Wang (ORCID: https://orcid.org/0000-0002-1515-9669)
- Lin Yang (ORCID: https://orcid.org/0000-0001-5049-7519)
- Jie Yang (ORCID: https://orcid.org/0000-0002-9032-5348)
- Guangfei Li (ORCID: https://orcid.org/0009-0000-4443-6269)
- Yanxin Wang (ORCID: https://orcid.org/0000-0002-3088-7584)
Institutions
- Peking University (CN)
- Beijing Jishuitan Hospital (CN)
- Beijing University of Technology (CN)
- Third People's Hospital of Yunnan Province (CN)
Publication Details
- Journal
- BioMedical Engineering OnLine
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1186/s12938-025-01436-y
- Primary Topic
- Cardiovascular Health and Disease Prevention
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Capital Medical University
- National Key Research and Development Program of China