WCN25-2743 THE PREDICTIVE PERFORMANCE AND USAGE OF ARTIFICIAL INTELLIGENCE (AI)-BASED FISTULA FAILURE MODEL IN SINGAPORE HEMODIALYSIS (HD) CLINICS
Arteriovenous fistulas (AVFs) are the preferred vascular access (VA) for Hemodialysis (HD) due to their longevity and lower risks of complications especially infection. AVF failure can lead to significant morbidity in HD patients, leading to setbacks in patient management. Thus, there is a substantial need to identify patients at risk for AVF failure [1]. Recently, Artificial Intelligence (AI) algorithms have been built using common clinical measurements to predict personalized Risk-based AVF failure.
Authors
- Benjamin Hippen (ORCID: https://orcid.org/0000-0003-1827-415X)
- Milind Nikam (ORCID: https://orcid.org/0000-0002-5040-2310)
- Francesco Bellocchio
- Jasmine Ion Titapiccolo (ORCID: https://orcid.org/0000-0001-5514-8182)
- Luca Neri (ORCID: https://orcid.org/0000-0001-5438-1329)
- Sugandha Saxena (ORCID: https://orcid.org/0000-0003-4226-9318)
- Franklin W. Maddux (ORCID: https://orcid.org/0000-0003-1395-2011)
- Tripti Singh (ORCID: https://orcid.org/0000-0002-8855-3421)
Institutions
- Fresenius Medical Care (United States) (US)
- Fresenius Medical Care North America (United States) (US)
- Fresenius Medical Care (Germany) (DE)
Publication Details
- Journal
- Kidney International Reports
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1016/j.ekir.2024.11.181
- Citations
- 1
- Primary Topic
- Trauma and Emergency Care Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.25