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Table 2 Diagnostic performance of different machine learning classifiers in validation cohort

From: Basal gonadotropin levels combine with pelvic ultrasound and pituitary volume: a machine learning diagnostic model of idiopathic central precocious puberty

Model

AUC

Accuracy

Sensitivity

Specificity

PPV

NPV

F1 score

XGBoost

0.81 (0.72–0.90)

0.68

0.81

0.72

0.80

0.59

0.80

LightGBM

0.78 (0.69–0.88)

0.69

0.72

0.76

0.77

0.60

0.73

Logistic

0.72 (0.61–0.83)

0.64

0.79

0.61

0.72

0.55

0.75

RandomForest

0.74 (0.70–0.86)

0.67

0.76

0.64

0.74

0.59

0.74

  1. AUC, area under curve; LightGBM, light gradient boosting; NPV, negative predictive value; PPV, positive predictive value; XGBoost, eXtreme Gradient Boosting
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BMC Pediatrics

ISSN: 1471-2431

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