Artificial intelligence-driven kidney organ allocation: systematic review of clinical outcome prediction, ethical frameworks, and decision-making algorithms.

ABSTRACT: Kidney transplantation remains the optimal treatment for end-stage renal disease, yet persistent organ shortages and inequitable allocation necessitate innovative solutions. Artificial intelligence (AI) and machine learning (ML) have emerged as promising tools for improving clinical outcomes and optimizing donor-recipient matching. However, their integration into clinical practice remains limited, and significant challenges regarding validation and ethical implementation persist. This systematic review synthesizes current research on AI-driven kidney allocation, focusing on predictive modeling, operational algorithms, and ethical considerations. We conducted a comprehensive literature search with no restrictions on publication year or country across biomedical databases (PubMed/MEDLINE, Em

SUBMITTER: Firuzpour F 

PROVIDER: S-EPMC12619412 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature