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Table 3 Sensitivity, specificity, post-test probability, and accuracy of six machine learning models for assessing the age of 18

From: Predicting chronological age of 14 or 18 in adolescents: integrating dental assessments with machine learning

 

LR

RF

DT

SVM

KNN

BNB

Sensitivity

0.776

0.770

0.761

0.760

0.769

0.778

Specificity

0.909

0.905

0.904

0.909

0.909

0.908

Post-test probability

0.851

0.844

0.842

0.851

0.852

0.851

Accuracy

0.806

0.796

0.796

0.807

0.804

0.806

  1. LR, Linear regression; RF, random forest; DT, decision tree; SVM, support vector machine; KNN, K-nearest neighbor; BNB, Bernoulli Naive Bayes
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BMC Pediatrics

ISSN: 1471-2431

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