Leveraging pulse wave signal properties for coronary artery calcification screening in CKD patients
Pulse wave analysis combined with machine learning offers a promising, non-invasive method for preliminary CAC screening in CKD patients. This approach could enhance early risk identification and improve clinical management, although further research is needed to validate and refine this method in larger, more diverse populations.
Authors
- Bengt Lindholm (ORCID: https://orcid.org/0000-0003-4269-4293)
- Małgorzata Dębowska (ORCID: https://orcid.org/0000-0001-8741-7930)
- Abdul Rashid Qureshi (ORCID: https://orcid.org/0000-0003-0536-5327)
- Peter Stenvinkel (ORCID: https://orcid.org/0000-0002-8785-4820)
- Torkel B. Brismar (ORCID: https://orcid.org/0000-0002-3409-1938)
- Jan Poleszczuk (ORCID: https://orcid.org/0000-0001-8758-7200)
- Leszek Pstras (ORCID: https://orcid.org/0000-0001-5705-6142)
- Jonaz Ripsweden (ORCID: https://orcid.org/0000-0003-2118-5414)
- Lu Dai (ORCID: https://orcid.org/0000-0001-9036-3857)
- Urszula Białończyk
- Magnus Söderberg (ORCID: https://orcid.org/0000-0003-0946-5202)
Institutions
- Stockholm University (SE)
- Karolinska Institutet (SE)
- AstraZeneca (Sweden) (SE)
- Baxter (Sweden) (SE)
- Institute of Biocybernetics and Biomedical Engineering (PL)
- Polish Academy of Sciences (PL)
Publication Details
- Journal
- Computers in Biology and Medicine
- Published
- 2025-06-06
- DOI
- https://doi.org/10.1016/j.compbiomed.2025.110519
- Citations
- 1
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 1.36