Empowering child health: Harnessing machine learning to predict acute respiratory infections in Ethiopian under-fives using demographic and health survey insights

Empowering child health: Harnessing machine learning to predict acute respiratory infections in Ethiopian under-fives using demographic and health survey insights

Abstract Background A dearth of studies showed that infectious diseases cause the majority of deaths among under-five children. Worldwide, Acute Respiratory Infection (ARI) continues to be the second most frequent cause of illness and mortality among children under the age of five. The paramount dis...

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Bibliographic Details
Main Authors: Mulugeta Hayelom Kalayou, Abdul-Aziz Kebede Kassaw, Kirubel Biruk Shiferaw
Format: Article
Language:English
Published: BMC 2024-03-01
Series:BMC Infectious Diseases
Subjects:
Acute respiratory infection
Artificial intelligence
Ethiopia
FAIR
Machine learning
Online Access:https://doi.org/10.1186/s12879-024-09195-2

Internet

https://doi.org/10.1186/s12879-024-09195-2

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