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Table 5 Model performance using the Braden scores

From: Modeling and prediction of pressure injury in hospitalized patients using artificial intelligence

AI technique

Original (row, imbalanced) data

Post-processed (rebalanced) cohorts

Model

Model

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LASSO linear regularized model

Performance of testing data

Model performance of testing data

 

Confusion matrix

Result false

Result true

Confusion matrix

Result false

Result true

 

Prediction false

4759

172

Prediction False

4202

38

 

Prediction true

14

68

Prediction True

571

202

 

Accuracy

96.29%

 

Accuracy

87.85%

 
 

95% CI

95.73%

96.80%

95% CI

86.92%

89.74%

 

Kappa

0.4079

 

Kappa

0.3514

 
 

Sensitivity

0.28333

 

Sensitivity

0.84167

 
 

Specificity

0.99707

 

Specificity

0.88037

 
 

Prevalence

0.01636

 

Prevalence

0.15420

 

Random forest

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Confusion matrix

Result false

Result true

Confusion matrix

Result false

Result true

Neural networks

Prediction false

6120

236

Prediction false

6058

225

 

Prediction true

99

110

Prediction true

161

121

 

Accuracy

94.897%

 

Accuracy

94.120%

 
 

Precision

0.5263

 

Precision

0.4291

 
 

AUC

0.7252

 

AUC

0.7134

 
 

Recall

0.3179

 

Recall

0.3497

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