Table 3 Performance evaluation of the radiomic models using SVM algorithm in the training and validation cohort

Training cohort

3D uncorrected

0.701

0.590

0.814

0.720

0.734

0.626

(0.690–0.718)

(0.570–0.622)

(0.796–0.831)

(0.700–0.735)

(0.702–0.754)

(0.602–0.637)

3D corrected

0.690

0.581

0.814

0.705

0.752

0.628

(0.680–0.702)

(0.556–0.607)

(0.792–0.834)

(0.694–0.721)

(0.720–0.776)

(0.583–0.611)

2D uncorrected

0.801

0.693

0.900

0.779

0.915

0.776

(0.800–0.821)

(0.681–0.715)

(0.886–0.932)

(0.771–0.799)

(0.910–0.932)

(0.772–0.791)

2D corrected

0.804

0.727

0.886

0.795

0.917

0.818

(0.793–0.815)

(0.706–0.742)

(0.855–0.900)

(0.784–0.803)

(0.896–0.925)

(0.797–0.829)

Validation cohort

3D uncorrected

0.640

0.431

0.864

0.602

0.750

0.531

(0.632–0.666)

(0.36–0.49)

(0.813–0.900)

(0.575–0.631)

(0.694–0.811)

(0.502–0.560)

3D corrected

0.640

0.432

0.861

0.601

0.750

0.514

(0.631–0.660)

(0.363–0.491)

(0.800–0.911)

(0.570–0.632)

(0.691–0.811)

(0.480–0.544)

2D uncorrected

0.790

0.709

0.860

0.710

0.852

0.729

(0.770–0.801)

(0.681–0.756)

(0.830–0.891)

(0.564–1.000)

(0.830–0.881)

(0.711–0.760)

2D corrected

0.796

0.714

0.872

0.753

0.848

0.787

(0.770–0.806)

(0.673–0.767)

(0.841–0.901)

(0.721–0.786)

(0.813–0.875)

(0.752–0.806)