Expert-augmented machine learning for predicting extubation readiness in the pediatric intensive care unit

Expert-augmented machine learning for predicting extubation readiness in the pediatric intensive care unit

Abstract Background Determining extubation readiness in pediatric intensive care units (PICU) is challenging. We used expert-augmented machine learning (EAML), a method that combines machine learning with human expert knowledge, to predict successful extubation. Methods We extracted electronic healt...

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Bibliographic Details
Main Authors: Jean Digitale, Deborah Franzon, Jin Ge, Charles McCulloch, Mark J. Pletcher, Efstathios D. Gennatas
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Expert-augmented machine learning
Clinical prediction model
Machine learning
Interpretability
Online Access:https://doi.org/10.1186/s12911-025-03070-z
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https://doi.org/10.1186/s12911-025-03070-z

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