AIMC Topic: Child Mortality

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A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Dec 1, 2019
OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infections residing in low- and middle-income countries, using age and other variables collected at hosp...
Humans Machine Learning Prospective Studies Prognosis Female Male Infant Severity of Illness Index Adolescent Rwanda Child, Preschool Child Hospital Mortality Age Factors Triage Developing Countries Child Mortality Sex Factors Infections Vital Signs
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