Personalized azithromycin treatment rules for children with watery diarrhea using machine learning

Personalized azithromycin treatment rules for children with watery diarrhea using machine learning

Abstract We use machine learning to identify innovative strategies to target azithromycin to the children with watery diarrhea who are most likely to benefit. Using data from a randomized trial of azithromycin for watery diarrhea (NCT03130114), we develop personalized treatment rules given sets of d...

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Main Authors: Sara S. Kim, Allison Codi, James A. Platts-Mills, Patricia B. Pavlinac, Karim Manji, Christopher R. Sudfeld, Christopher P. Duggan, Queen Dube, Naor Bar-Zeev, Karen Kotloff, Samba O. Sow, Sunil Sazawal, Benson O. Singa, Judd Walson, Farah Qamar, Tahmeed Ahmed, Ayesha De Costa, David Benkeser, Elizabeth T. Rogawski McQuade
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-60682-9
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https://doi.org/10.1038/s41467-025-60682-9

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