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What is Machine Learning for Sepsis Detection about?

This study developed and validated a machine learning model using the eXtreme Gradient Boosting (XGBoost) algorithm to identify sepsis patients in the emergency department (ED), outperforming traditional clinical tools like SIRS and qSOFA. The model was trained on clinical data from two hospitals, achieving an AUROC of 0.86 in internal validation and 0.75 in external validation, indicating good discriminative capabilities despite some performance deterioration due to patient heterogeneity. The findings emph

Author

Jayme Mattos de Souza

Language

EN