Table 1.
The latest computational models in lung cancer.
Table 2.
Comparison of Sample Sizes in Various Studies.
Fig 1.
The modelling process framework.
This is a structured flowchart outlining a machine learning pipeline for classifying lung conditions from CT scans, including preprocessing, segmentation, feature extraction, modeling, and classification into six classes.
Fig 2.
This figure shows a CT scan (left) and its corresponding segmentation mask (right), representing the two input modalities to the proposed DbMCA model. The mask isolates the lung region, enabling focused feature extraction for downstream analysis.
Fig 3.
The Proposed Model - Dual-Branch Model Classification Approach (DbMCA).
This diagram illustrates the DbMCA architecture comprising two parallel branches: a CNN pipeline (left) with four stages and 19 steps for processing image inputs, and a DNN pipeline (right) with seven steps for processing mask inputs. Outputs from both branches are concatenated and passed through a SoftMax layer for final classification into 6 classes of cancer level.
Table 3.
Metrics values (Accuracy, F1 Score, Recall, and Precession) – Experiment 1.
Table 4.
Metrics values (Accuracy, F1 Score, Recall, and Precession) – Experiment 2.
Fig 4.
Comparison of Metrics Results for all Models for Experiment 1 (20k).
This bar chart compares the proposed Dual-Branch Model Classification Approach (DbMCA) against CNN, DNN, and SVM models using image and mask inputs. Metrics include Precision, Recall, F1 Score, and Accuracy. DbMCA achieved the highest overall performance, with 91.21% accuracy and balanced precision and recall across modalities.
Fig 5.
Comparison of Metrics Results for all Models for Experiment 2 (5k).
This bar chart compares the proposed Dual-Branch Model Classification Approach (DbMCA) against CNN, DNN, and SVM models using image and mask inputs. Metrics include Precision, Recall, F1 Score, and Accuracy. DbMCA achieved the highest overall performance, with 98.04% accuracy and balanced precision and recall across modalities.
Table 5.
Paired T-Test Results Summary (Experiment 1).
Table 6.
Table 5- Paired T-Test Results Summary (Experiment 2).