Machine learning approaches to identify neonates and young children at risk for postdischarge mortality in Dar es Salaam, Tanzania and Monrovia, Liberia

Machine learning approaches to identify neonates and young children at risk for postdischarge mortality in Dar es Salaam, Tanzania and Monrovia, Liberia

Background The time after hospital discharge carries high rates of mortality in neonates and young children in sub-Saharan Africa. Previous work using logistic regression to develop risk assessment tools to identify those at risk for postdischarge mortality has yielded fair discriminatory value. Our...

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Main Authors: Rodrick Kisenge, Todd A. Florin, Cynthia G. Whitney, Michelle Niescierenko, Julia Kamara, Abraham Samma, Evance Godfrey, Chris A. Rees, Readon C. Ideh, Ye-Jeung G. Coleman-Nekar, Hussein K. Manji, Christopher R. Sudfeld, Adrianna L. Westbrook, Claudia R. Morris, Karim P. Manji, Christopher P. Duggan, Rishikesan Kamaleswaran
Format: Article
Language:English
Published: BMJ Publishing Group 2025-06-01
Series:BMJ Paediatrics Open
Online Access:https://bmjpaedsopen.bmj.com/content/9/1/e003547.full
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https://bmjpaedsopen.bmj.com/content/9/1/e003547.full

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