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Table 2 Comparison of the predictive performance of clinical model, radiomics models, and joint models

From: The predictive value of [18F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma

 

AUC

95% CI low

95% CI up

Best threshold

Specificity

Sensitivity

Accuracy

Training set

Clinical model

0.738

0.688

0.788

0.643

0.683

0.708

0.698

CT_RF

0.688

0.637

0.739

0.635

0.714

0.547

0.614

CT joint model

0.773

0.727

0.818

0.638

0.795

0.638

0.701

PET_RF

0.666

0.613

0.719

0.525

0.615

0.670

0.649

PET joint model

0.743

0.694

0.792

0.533

0.590

0.794

0.713

PET/CT_RF

0.698

0.647

0.749

0.549

0.739

0.564

0.634

PET/CT joint model

0.760

0.713

0.807

0.573

0.683

0.733

0.713

Testing set

Clinical model

0.681

0.577

0.782

0.538

0.634

0.686

0.667

CT_RF

0.726

0.629

0.822

0.596

0.756

0.643

0.685

CT joint model

0.723

0.628

0.818

0.504

0.683

0.671

0.676

PET_RF

0.678

0.572

0.785

0.504

0.659

0.643

0.649

PET joint model

0.703

0.601

0.806

0.575

0.634

0.686

0.667

PET/CT_RF

0.704

0.603

0.804

0.426

0.561

0.800

0.712

PET/CT joint model

0.730

0.633

0.828

0.491

0.585

0.786

0.712

  1. AUC area under the curve; CI confidence interval; RF random forest