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Table 5 Performance of the optimal models via tenfold cross validation

From: Hyperglycemia screening based on survey data: an international instrument based on WHO STEPs dataset

Models

 

Accuracy

Specificity

Sensitivity

AUC

F1-Score

RF Type D

Mean

0.7047

0.7075

0.6978

0.7027

0.5835

95% CI

(0.69, 0.72)

(0.69, 0.72)

(0.68, 0.71)

(0.69, 0.71)

(0.57, 0.6)

SD

0.0178

0.0207

0.024

0.0178

0.021

XGB Type D

Mean

0.6962

0.6837

0.7258

0.7048

0.5861

95% CI

(0.69, 0.71)

(0.67, 0.69)

(0.71, 0.74)

(0.69, 0.72)

(0.57, 0.6)

SD

0.0177

0.0168

0.0233

0.0189

0.0215

SVM Type C

Mean

0.7001

0.6985

0.7039

0.7012

0.5818

95% CI

(0.69, 0.71)

(0.69, 0.71)

(0.69, 0.72)

(0.69, 0.71)

(0.57, 0.59)

SD

0.0151

0.0161

0.0219

0.0159

0.0185

LR Type C

Mean

0.7021

0.7022

0.702

0.7021

0.5827

95% CI

(0.69, 0.71)

(0.69, 0.71)

(0.69, 0.72)

(0.69, 0.71)

(0.57, 0.59)

SD

0.0143

0.013

0.0241

0.0164

0.0192

ANN1 Type C

Mean

0.6981

0.6914

0.7142

0.7028

0.5837

95% CI

(0.69, 0.71)

(0.68, 0.7)

(0.7, 0.73)

(0.69, 0.71)

(0.57, 0.6)

SD

0.016

0.0171

0.0276

0.0178

0.0207

ANN2 Type D

Mean

0.6968

0.689

0.7152

0.7021

0.583

95% CI

(0.69, 0.71)

(0.68, 0.7)

(0.71, 0.73)

(0.69, 0.71)

(0.57, 0.59)

SD

0.0157

0.0192

0.0163

0.0144

0.0166

  1. ANN1 = ANN model with 1 hidden layer; ANN2 = ANN model with 2 hidden layers