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Table 3 Statistical quantitative description of the numeric features

From: Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone

 

Full sample

Dead patients

Survived patients

Numeric feature

Median

Mean

σ

Median

Mean

σ

Median

Mean

σ

Age

60.00

60.83

11.89

65.00

65.22

13.21

60.00

58.76

10.64

Creatinine phosphokinase

250.00

581.80

970.29

259.00

670.20

1316.58

245.00

540.10

753.80

Ejection fraction

38.00

38.08

11.83

30.00

33.47

12.53

38.00

40.27

10.86

Platelets

262.00

263.36

97.80

258.50

256.38

98.53

263.00

266.66

97.53

Serum creatinine

1.10

1.39

1.03

1.30

1.84

1.47

1.00

1.19

0.65

Serum sodium

137.00

136.60

4.41

135.50

135.40

5.00

137.00

137.20

3.98

Time

115.00

130.30

77.61

44.50

70.89

62.38

172.00

158.30

67.74

  1. Full sample: 299 individuals. Dead patients: 96 individuals. Survived patients: 203 individuals. σ: standard deviation