A machine learning approach for identification of vascular access patency in hemodialysis patients using photoplethysmography: A pilot study
Our approach can provide reliable classifications for VA patency. It is effective to use the proposed PPG signal features to predict 6-month PP of VA.
Authors
- Chuan‐Yu Chang (ORCID: https://orcid.org/0000-0001-9476-8130)
- Chin‐Chung Tseng (ORCID: https://orcid.org/0000-0002-8445-5269)
- Ming‐Long Yeh (ORCID: https://orcid.org/0000-0001-6942-060X)
- Po-Kai Yang (ORCID: https://orcid.org/0000-0002-1706-6773)
- Hong-Xu Zhuo
- Wen-Fong Wang
- Danyal Shahmirzadi
Institutions
- National Cheng Kung University Hospital (TW)
- National Yunlin University of Science and Technology (TW)
- National Cheng Kung University (TW)
Publication Details
- Journal
- The Journal of Vascular Access
- Published
- 2024-12-26
- DOI
- https://doi.org/10.1177/11297298241304467
- Citations
- 1
- Primary Topic
- Central Venous Catheters and Hemodialysis
- Type
- article
- Field-Weighted Citation Impact
- 0.74
Funders
- National Cheng Kung University Hospital