Transforming nephrology through artificial intelligence: a state-of-the-art roadmap for clinical integration - PubMed

3 days ago

AI is set to transform nephrology by enabling early detection, precise risk stratification, and clinical decision support.
Applications of AI in nephrology include acute kidney injury (AKI), chronic kidney disease (CKD), dialysis, and kidney transplantation.
In AKI, predictive models show strong performance but face challenges in clinical workflow integration.
In CKD, machine learning aids in risk stratification and personalized therapy planning.
AI enhances dialysis management by optimizing ultrafiltration, anemia control, and vascular access surveillance.
Generative AI and large language models improve clinical documentation, triage, and patient education.
In transplantation, AI assists in organ allocation, graft monitoring, and rejection classification.
Challenges include data heterogeneity, bias, interpretability, regulatory uncertainty, and workflow integration.
Future directions include multimodal data integration, reinforcement learning, digital twins, and ambient intelligence.
Regulatory frameworks are evolving, emphasizing clinician involvement in AI model development and deployment.

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