Table 2 Sensitivity and specificity of prediction models for in-hospital and out-of-hospital mortality in the training set and verification set

Death in hospital

Newly Developed Machine Learning Models

ANN

7

0.78(0.57,0.91)

0.92(0.87,0.95)

1

0.84

0.93

DT

6

0.83(0.67,0.92)

0.93(0.78,0.98)

2

0.44-1

0.98–0.98

KNN

1

0.91

LR

9

0.68(0.58,0.77)

0.91(0.85,0.95)

2

0.59–0.66

0.92–0.94

RF

7

0.86(0.73,0.93)

0.92(0.76,0.98)

SVM

12

0.86(0.80,0.91)

0.87(0.74,0.94)

1

0.66

0.95

NB

6

0.82(0.74,0.87)

0.89(0.70,0.96)

1

0.59

0.89

LDA

2

0.66–0.85

0.48–0.81

GBM

3

0.76–0.94

0.63–0.81

LASSO

1

0.95

0.48

Ridge

1

0.88

0.71

AdaBoost

1

0.34

0.97

xgboost

1

0.79

0.81

Other

7

0.67(0.50,0.80)

0.88(0.65,0.97)

Overall

64

0.79(0.75,0.82)

0.89(0.86,0.92)

7

0.64(0.53,0.75)

0.95(0.92,0.97)

Mature Clinically Recommended Tools

CRASH core

1

0.73

0.90

CRASH CT

2

0.72–0.84

0.72–0.90

CRASH base

2

0.72–0.78

0.80–0.82

Helsinki

1

0.83

0.59

1

0.66

0.84

Marshall

1

0.75

0.98

1

0.50

0.99

Total GCS

2

0.50–0.51

0.90–0.90

Rotterdam

1

0.58

0.77

1

0.66

0.64

IMPACT ct

1

0.80

0.78

Overall

11

0.71(0.64,0.78)

0.84(0.78,0.89)

Death within 1 month

Newly Developed Machine Learning Models

DT

1

0.71

0.77

LR

2

0.70–0.77

0.61–0.75

RF

1

0.80

0.84

SVM

LASSO/Rige

Overall

4

0.74(0.67,0.81)

0.75(0.66,0.82)

Mature Clinically Recommended Tools

CRASH core

1

0.77

0.89

CRASH CT

1

0.87

0.88

Total GCS

1

0.60

0.70

APACHE II

1

0.75

0.75

IMPACT core

1

0.70

0.74

IMPACT extended

1

0.76

0.74

IMPACT lab

1

0.72

0.76

Overall

7

0.75(0.68,0.80)

0.79(0.73,0.84)