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Table 4 Results from PRBF algorithm from experts D1-D4. A) Cross-validation model training results for PRBF algorithm for Population size = 4000, stretch = 25, learning rate = 0.1, and training iterations = 100,000, B) True labels and predicted uncertain labels for the tested SFRP sample of fictitious patient number 72

From: Toward a hemorrhagic trauma severity score: fusing five physiological biomarkers

A

 

Training accuracy

Test accuracy

Fold-1

0.95

0.90

Fold-2

0.96

0.90

Fold-3

0.98

0.95

Fold-4

0.95

0.95

Fold-5

0.94

0.90

Mean accuracy

0.96

0.92

Standard deviation

± 0.01

± 0.03

B

Fictitious patient

Majority vote

Uncertain label (\({\text{u}}\))

PRBF prediction (\(\pi\))

72

0

[1,0.5,0,0,0]

[0.979,0.321,0,0,0]