Fig 1.
Illustration of the systematic workflow employed in this study.
Fig 2.
The LC25000 dataset where (a) adenocarcinoma, (b) benign, and (c) squamous cell carcinoma.
Fig 3.
The proposed XLLC-Net architecture.
Table 1.
Summary of the proposed model, detailing the number of parameters and characteristics of each layer.
Table 2.
Hyper-parameters employed for training XLLC-Net.
Table 3.
Specifications of the system used for the proposed framework.
Table 4.
Performance metrics (Accuracy, Precision, Recall, and F1-score) for five independent training trials of the XLLC-Net model.
Table 5.
Performance comparison of different DL models in predicting cancer types.
Fig 4.
Performance of the proposed model against various DL models.
Table 6.
Performance of the proposed model against various DL models.
Table 7.
State-of-the-art comparison between proposed model and previous models on lung histopathological data.
Fig 5.
Comparison of training and validation accuracy across epochs for several pre-trained models, including (a) AlexNet, (b) ResNet50, (c) VGG16, and (d) VGG19.
Fig 6.
Training and validation accuracy across epochs for our proposed XLLC-Net model. (a) 1st Trial, (b) 2nd Trial, (c) 3rd Trial, (d) 4th Trial, (e) 5th Trial.
Fig 7.
Comparison of training and validation loss across epochs for several pre-trained models, including (a) AlexNet, (b) ResNet50, (c) VGG16, and (d) VGG19.
Fig 8.
Training and validation loss across epochs for our proposed XLLC-Net model. (a) 1st Trial, (b) 2nd Trial, (c) 3rd Trial, (d) 4th Trial, (e) 5th Trial.
Fig 9.
Comparison of AUC for various pre-trained models, including (a) AlexNet, (b) ResNet50, (c) VGG16, and (d) VGG19.
Fig 10.
AUC for our proposed XLLC-Net model across five independent trials. (a) 1st Trial, (b) 2nd Trial, (c) 3rd Trial, (d) 4th Trial, (e) 5th Trial.
Fig 11.
Comparison of confusion matrix for several pre-trained models, including (a) AlexNet, (b) ResNet50, (c) VGG16, and (d) VGG19.
Fig 12.
Confusion matrices of the XLLC-Net model across five independent trials. (a) 1st Trial, (b) 2nd Trial, (c) 3rd Trial, (d) 4th Trial, (e) 5th Trial.
Fig 13.
Saliency map of squamous cell carcinoma.
Fig 14.
Saliency map of benign.
Fig 15.
Saliency map of adenocarcinoma.
Fig 16.
GradCAM of squamous cell carcinoma.
Fig 17.
GradCAM of benign.
Fig 18.
GradCAM of adenocarcinoma.