Artificial intelligence in kidney disease and dialysis: from data mining to clinical impact
AI in nephrology shows promise for personalized care and cost reduction, as demonstrated by tools like the Anemia Control Model. Yet, broad adoption requires rigorous validation, seamless workflow integration, regulatory clearance, and clinician trust. Future opportunities include digital twins, large language models, and multiomics integration, with AI poised to enhance both patient outcomes and system performance.
Authors
- Hanjie Zhang (ORCID: https://orcid.org/0000-0002-0015-5614)
- Len A. Usvyat (ORCID: https://orcid.org/0000-0003-2745-1429)
- Luca Neri (ORCID: https://orcid.org/0000-0001-5438-1329)
Institutions
- Associated Research (United States) (US)
- Renal Research Institute (US)
- New York University (US)
Publication Details
- Journal
- Current Opinion in Nephrology & Hypertension
- Published
- 2025-11-07
- DOI
- https://doi.org/10.1097/mnh.0000000000001132
- Citations
- 2
- Primary Topic
- Dialysis and Renal Disease Management
- Type
- article
- Field-Weighted Citation Impact
- 2.86