Table 2 Performance metrics of ResNet50 and ResNet50v2 with optimizers SAM and SGD continuity analysis.

From: Deep learning model for analyzing the relationship between mandibular third molar and inferior alveolar nerve in panoramic radiography

CNN

Optimizer

Accuracy

Precision

Recall

F1 score

AUC

SD

SD

SD

SD

SD

95% CI

95% CI

95% CI

95% CI

95% CI

ResNet50

SAM

0.754

0.755

0.754

0.753

0.832

0.005

0.008

0.008

0.008

0.006

0.753–0.756

0.752–0.757

0.751–0.757

0.750–0.755

0.829–0.834

ResNet50

SGD

0.754

0.754

0.754

0.752

0.830

0.007

0.008

0.008

0.008

0.006

0.752–0.757

0.752–0.757

0.751–0.757

0.750–0.755

0.827–0.832

ResNet50v2

SAM

0.766

0.766

0.765

0.775

0.843

0.007

0.006

0.006

0.013

0.005

0.764–0.769

0.764–0.768

0.763–0.767

0.771–0.780

0.842–0.845

ResNet50v2

SGD

0.765

0.765

0.765

0.767

0.842

0.006

0.006

0.006

0.013

0.005

0.763–0.768

0.763–0.767

0.762–0.767

0.762–0.772

0.840–0.844

  1. SD, standard deviation; 95% CI, 95% confidence interval; AUC, area under the receiver operating characteristics curve.