Outcomes and predictive models
|
Accuracy
|
Precision
|
Sensitivity
|
Specificity
|
F1
|
AUC
|
---|
AMI < 1 month
|
Random forest
|
0.915
|
0.916
|
0.915
|
0.882
|
0.915
|
0.915
|
Logistic regression
|
0.868
|
0.885
|
0.868
|
0.766
|
0.867
|
0.868
|
SVC
|
0.631
|
0.635
|
0.631
|
0.538
|
0.627
|
0.631
|
KNN
|
0.865
|
0.880
|
0.865
|
0.766
|
0.864
|
0.865
|
All-cause mortality < 1 month
|
Random forest
|
0.999
|
0.999
|
0.999
|
1.000
|
0.999
|
0.999
|
Logistic regression
|
0.716
|
0.717
|
0.716
|
0.690
|
0.716
|
0.716
|
SVC
|
0.656
|
0.660
|
0.656
|
0.584
|
0.654
|
0.656
|
KNN
|
0.969
|
0.971
|
0.969
|
0.940
|
0.969
|
0.969
|
- SVC support-vector clustering; KNN K-nearest neighbors; ED emergency department; F1 2 x (precision x recall/precision + recall); AUC area under the curve; AMI acute myocardial infarction