Utilization of Machine Learning Approaches to Predict Mortality in Pediatric Warzone Casualties
- Daniel Lammers; James Williams; Jeff Conner; Andrew Francis; Beau Prey; Christopher Marenco
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This article describes using machine learning to predict the risk of death in children injured in warzones. Researchers used data from 2,007 patients and tested different models like random forest and neural networks. The study found that these models could help identify high-risk patients better than traditional methods. This can improve care by helping doctors make faster decisions about treatment and resource allocation, especially in areas with limited medical resources. While promising, the study suggests more research is needed before these tools are used directly in hospitals or on battlefields.
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