Predicting acute kidney injury with an artificial intelligence-driven model in a pediatric cardiac intensive care unit

Predicting acute kidney injury with an artificial intelligence-driven model in a pediatric cardiac intensive care unit

Abstract Background Acute kidney injury (AKI) is among the most common complications following cardiac surgery in adult and pediatric patients, significantly affecting morbidity and mortality. Artificial Intelligence (AI) with Machine Learning (ML) can be used to predict outcomes. AKI diagnosis anti...

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Bibliographic Details
Main Authors: Tiziana Fragasso, Valeria Raggi, Davide Passaro, Luca Tardella, Giovanna Jona Lasinio, Zaccaria Ricci
Format: Article
Language:English
Published: BMC 2023-10-01
Series:Journal of Anesthesia, Analgesia and Critical Care
Subjects:
Acute kidney injury
Machine learning
Pediatric cardiac intensive care unit
Risk factors
Predictive models
Electronic health record
Online Access:https://doi.org/10.1186/s44158-023-00125-3

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