Fig. 3: Classification performance of final model on testing set (n= 499). | Nature Communications

Fig. 3: Classification performance of final model on testing set (n= 499).

From: Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram

Fig. 3

This figure compares the area under ROC curve (95% confidence interval) between our machine learning (ML) fusion model against experienced clinicians and against rule-based commercial interpretation software for detecting a any acute coronary syndrome (ACS) event, and b non-ST elevation acute coronary syndrome events (NSTE-ACS). ***p < 0.001 using two-sided DeLong’s nonparametric approach.

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