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Machine learning approach for dosage individualization of azithromycin in children with community‐acquired pneumonia

The uncertainty about the efficacy and safety of currently used azithromycin dosing regimens in children warrants individualized therapy. The area under the plasma concentration‐time curve over 24 h (AUC0‐24) of azithromycin… Click to show full abstract

The uncertainty about the efficacy and safety of currently used azithromycin dosing regimens in children warrants individualized therapy. The area under the plasma concentration‐time curve over 24 h (AUC0‐24) of azithromycin correlates best with its effectiveness. The aim of this study was to evaluate the ability of machine learning (ML) to predict the AUC0‐24 of azithromycin in children with community‐acquired pneumonia.

Keywords: community acquired; azithromycin children; machine learning; children community; acquired pneumonia

Journal Title: British Journal of Clinical Pharmacology
Year Published: 2025

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