Innovative Approaches to Clinical Diagnosis: Transfer Learning in Facial Image Classification for Celiac Disease Identification
Abstract
:1. Introduction
2. Background and Related Work
2.1. Machine Learning and Deep Neural Network
2.2. Transfer Learning
3. Materials and Method
3.1. Collection and Preparation of Datasets
3.2. The Workflow
3.2.1. Image Preprocessing
3.2.2. Model Configuration
3.2.3. Adding Custom Layers
3.2.4. Compilation
3.2.5. Data Augmentation
3.2.6. Data Generators
3.2.7. Training Loop
3.2.8. Evaluation and Metrics
3.2.9. Visualization
3.2.10. Classification Report and Confusion Matrix
4. Results
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Model | Total Parameters | Trainable | Non-Trainable |
---|---|---|---|
Customized Model | 39,805,690 | 25,091,002 | 14,714,688 |
No. of Epoch | Learning Rate | Testing Loss | Testing Accuracy | Validation Loss | Validation Accuracy |
---|---|---|---|---|---|
Epoch 1/10 | 15 s 3 s/step | 6.2137 | 0.5000 | 6.2114 | 0.5000 |
Epoch 2/10 | 16 s 3 s/step | 2.0953 | 0.5217 | 2.1691 | 0.5100 |
Epoch 3/10 | 15 s 3 s/step | 1.7656 | 0.5669 | 1.7505 | 0.5500 |
Epoch 4/10 | 16 s 3 s/step | 0.8504 | 0.7587 | 0.9814 | 0.7300 |
Epoch 5/10 | 15 s 3 s/step | 0.9370 | 0.7054 | 0.7952 | 0.7400 |
Epoch 6/10 | 16 s 3 s/step | 0.6226 | 0.7319 | 0.6401 | 0.7100 |
Epoch 7/10 | 15 s 3 s/step | 0.6660 | 0.7668 | 0.7453 | 0.7400 |
Epoch 8/10 | 15 s 3 s/step | 0.5976 | 0.7720 | 0.6835 | 0.7400 |
Epoch 9/10 | 20 s 5 s/step | 0.5129 | 0.7398 | 0.5192 | 0.7400 |
Epoch 10/10 | 16 s 3 s/step | 0.6034 | 0.7305 | 0.6018 | 0.7300 |
Precision | Recall | F1 Score | Support | |
---|---|---|---|---|
Celiac | 0.57 | 0.56 | 0.52 | 50 |
Nonceliac | 0.54 | 0.70 | 0.61 | 50 |
Accuracy | 0.55 | 100 | ||
Macro Avg | 0.55 | 0.55 | 0.54 | 100 |
Weighted Avg | 0.55 | 0.55 | 0.54 | 100 |
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Keskin Bilgiç, E.; Zaim Gökbay, İ.; Kayar, Y. Innovative Approaches to Clinical Diagnosis: Transfer Learning in Facial Image Classification for Celiac Disease Identification. Appl. Sci. 2024, 14, 6207. https://doi.org/10.3390/app14146207
Keskin Bilgiç E, Zaim Gökbay İ, Kayar Y. Innovative Approaches to Clinical Diagnosis: Transfer Learning in Facial Image Classification for Celiac Disease Identification. Applied Sciences. 2024; 14(14):6207. https://doi.org/10.3390/app14146207
Chicago/Turabian StyleKeskin Bilgiç, Elif, İnci Zaim Gökbay, and Yusuf Kayar. 2024. "Innovative Approaches to Clinical Diagnosis: Transfer Learning in Facial Image Classification for Celiac Disease Identification" Applied Sciences 14, no. 14: 6207. https://doi.org/10.3390/app14146207
APA StyleKeskin Bilgiç, E., Zaim Gökbay, İ., & Kayar, Y. (2024). Innovative Approaches to Clinical Diagnosis: Transfer Learning in Facial Image Classification for Celiac Disease Identification. Applied Sciences, 14(14), 6207. https://doi.org/10.3390/app14146207