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Table 4 Comparison of predicting the ICU admission and all-cause mortality rates between the AI model using MLP and the PHD score

From: Using artificial intelligence to predict adverse outcomes in emergency department patients with hyperglycemic crises in real time

All-cause mortality

Accuracy

Sensitivity

Specificity

PPV

NPV

F1

AUC

p-value*

MLP model

0.776

0.637

0.797

0.314

0.938

0.421

0.796

 < 0.001

PHD score

0.670

0.637

0.675

0.223

0.927

0.330

0.693

ICU admission

Accuracy

Sensitivity

Specificity

PPV

NPV

F1

AUC

p-value

MLP model

0.809

0.521

0.827

0.161

0.964

0.246

0.743

0.084

PHD score

0.671

0.521

0.681

0.094

0.957

0.160

0.641

  1. ICU Intensive care unit, AI Artificial intelligence, MLP Multilayer perceptron, PHD Predicting the hyperglycemic crisis death, PPV Positive predictive value, NPV Negative predictive value; F1, 2 × (precision × recall/precision + recall), AUC Area under the curve
  2. *The DeLong test was used to compare the AUC between MLP model and PHD score [27]. Note: We adjusted the classification threshold to approach the same level of sensitivity as the prediction using the PHD score