Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score

Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score

Traumatic injuries are a leading cause of morbidity and mortality globally, with a disproportionate impact on populations in low- and middle-income countries (LMICs). The Kampala Trauma Score (KTS) is frequently used for triage in these settings, though its predictive accuracy remains under debate. This study evaluates the effectiveness of machine learning (ML) models in predicting triage decisions and compares their performance to the KTS.

Mike Nsubuga, Timothy Mwanje Kintu, Helen Please, Kelsey Stewart & Sergio M. Navarro

https://link.springer.com/article/10.1186/s12873-025-01175-2

https://link.springer.com/journal/12873

23 january 2025

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