Table 2 Comparison results of all models.

From: An interpretable machine learning-assisted diagnostic model for Kawasaki disease in children

Model

Accuracy

Sensitivity

Specificity

Precision

F1-score

KNN

0.8968

0.8947

0.9003

0.9379

0.9158

LR

0.9037

0.9166

0.8819

0.9288

0.9227

SVM

0.9078

0.9232

0.8819

0.9293

0.9262

DT

0.883

0.8969

0.8597

0.9149

0.9058

MLP

0.9105

0.9254

0.8856

0.9315

0.9284

RF

0.9202

0.9407

0.8856

0.9326

0.9366

AdaBoost

0.9284

0.9473

0.8966

0.9391

0.9432

CatBoost

0.9312

0.9451

0.9077

0.9451

0.9451

GBDT

0.9284

0.9364

0.9151

0.9488

0.9426

XGBoost

0.9381

0.9517

0.9151

0.9496

0.9507

Back to article page