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A Hybrid AutoML Ensemble Integrating Conventional Learners and Gradient-Boosting Models for Multi-Outcome Prediction in ICU Patients with <i>Pseudomonas aeruginosa</i>

2025-06-20

Abstract excerpt

<h4>Background</h4> Carbapenem resistance in Pseudomonas aeruginosa is increasing in intensive care units (ICUs). To enhance antimicrobial stewardship and infection control, we aimed to develop and validate a real-time interpretable hybrid Automated Machine Learning (AutoML) ensemble for multi-outcome prediction. <h4>Methods</h4> We retrospectively analyzed 847 adult ICU admissions with P. aeruginosa isol ate...

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Literature Corpus work: 3a77bfc8-c7cb-5ef6-ad89-8ee43141df96
DOI: 10.1101/2025.06.19.25329970

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