Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Training and validation loss & accuracy curve—DenseNet121 (Epochs = 20, Batch Size = 64) Kaggle Binary Class OSCC Dataset.

Article Snippet: Fig. 21 Training and validation loss & accuracy curve—DenseNet121 (Epochs = 20, Batch Size = 64) Kaggle Binary Class OSCC Dataset.

Techniques: Biomarker Discovery

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Training and validation loss & accuracy curve—DenseNet121 (Epochs = 20, Batch Size = 64) NDB-UFES Multiclass OSCC Dataset.

Article Snippet: Fig. 21 Training and validation loss & accuracy curve—DenseNet121 (Epochs = 20, Batch Size = 64) Kaggle Binary Class OSCC Dataset.

Techniques: Biomarker Discovery

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Proposed deep visual detection system using DenseNet121 for binary classification on the Kaggle OSCC dataset.

Article Snippet: DenseNet121 showed moderate performance, especially on the Kaggle dataset with 86.91% accuracy, but failed to generalize effectively on the more complex NDB-UFES dataset.

Techniques:

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Key Hyperparameters of the DenseNet121 model (Kaggle Binary Class OSCC Dataset).

Article Snippet: DenseNet121 showed moderate performance, especially on the Kaggle dataset with 86.91% accuracy, but failed to generalize effectively on the more complex NDB-UFES dataset.

Techniques:

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Key Hyperparameters of the DenseNet121 model (NDB-UFES Multiclass OSCC Dataset).

Article Snippet: DenseNet121 showed moderate performance, especially on the Kaggle dataset with 86.91% accuracy, but failed to generalize effectively on the more complex NDB-UFES dataset.

Techniques:

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Training and validation loss & accuracy curve—DenseNet121 (Epochs = 20, Batch Size = 64) Kaggle Binary Class OSCC Dataset.

Article Snippet: DenseNet121 showed moderate performance, especially on the Kaggle dataset with 86.91% accuracy, but failed to generalize effectively on the more complex NDB-UFES dataset.

Techniques: Biomarker Discovery

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Training and validation loss & accuracy curve—DenseNet121 (Epochs = 20, Batch Size = 64) NDB-UFES Multiclass OSCC Dataset.

Article Snippet: DenseNet121 showed moderate performance, especially on the Kaggle dataset with 86.91% accuracy, but failed to generalize effectively on the more complex NDB-UFES dataset.

Techniques: Biomarker Discovery

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Confusion matrix of DenseNet121 model (Epochs = 20, Batch Size = 64)—Kaggle Binary Class OSCC dataset.

Article Snippet: DenseNet121 showed moderate performance, especially on the Kaggle dataset with 86.91% accuracy, but failed to generalize effectively on the more complex NDB-UFES dataset.

Techniques:

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Confusion matrix of DenseNet121 model (Epochs = 20, Batch Size = 64)—NDB-UFES Multiclass OSCC dataset.

Article Snippet: DenseNet121 showed moderate performance, especially on the Kaggle dataset with 86.91% accuracy, but failed to generalize effectively on the more complex NDB-UFES dataset.

Techniques:

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Performance comparison of EfficientNetB3, DenseNet121, and ResNet50 on Kaggle Binary-Class and NDB-UFES multiclass OSCC datasets.

Article Snippet: DenseNet121 showed moderate performance, especially on the Kaggle dataset with 86.91% accuracy, but failed to generalize effectively on the more complex NDB-UFES dataset.

Techniques: Comparison