Abstract

Over the past decade, artificial intelligence (AI) through machine learning (ML) has been increasingly used in health care applications. The use of AI/ML to enhance the provision of continuous kidney replacement therapy (CKRT) is an area of active investigation because of the growing clinical needs of critically ill patients and the abundance of multimodal data from the electronic health records (EHRs) and the CKRT machine itself. Importantly, best clinical practices of CKRT have not been sufficiently standardized, so there is considerable heterogeneity in utilization and deliverables. In this context, AI/ML-based tools could facilitate informed decisions to enhance CKRT goal-oriented deliver- ables and resource allocation and improve outcomes relevant to patients. In this brief review, we discuss potential applications of AI/ML in CKRT.

Document Type

Article

Publication Date

5-2023

Notes/Citation Information

Copyright © 2023 by the American Society of Nephrology

Digital Object Identifier (DOI)

https://doi.org/10.2215/CJN.0000000000000099

Funding Information

National Institute of Diabetes and Digestive and Kidney Diseases grant R56 DK126930. J.A. Neyra is currently supported by National Institute of Diabetes and Digestive and Kidney Diseases grants R01DK128208 and U01DK129989.

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