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README.md
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@@ -22,19 +22,19 @@ A VGG16 model fine-tuned for binary classification of chest X-ray images.
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## Model Performance
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| Metric | Value |
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|--------|-------|
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| AUC-ROC | 0.
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| Accuracy | 0.
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| F1-Score | 0.
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| Recall | 0.
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| Specificity | 0.
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| Precision | 0.
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## Training Details
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- **Base Model:** VGG16 (ImageNet pre-trained)
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- **Fine-tuning:** 2-phase (feature extraction + fine-tuning)
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- **Dataset:** RSNA Pneumonia Detection Challenge (26,684 patients)
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- **Input Size:** 224x224x3
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- **Optimal Threshold:** 0.
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## Usage
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```python
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## Model Performance
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| Metric | Value |
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|--------|-------|
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| AUC-ROC | 0.8625 |
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| Accuracy | 0.7734 |
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| F1-Score | 0.6116 |
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| Recall | 0.7916 |
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| Specificity | 0.7681 |
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| Precision | 0.4983 |
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## Training Details
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- **Base Model:** VGG16 (ImageNet pre-trained)
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- **Fine-tuning:** 2-phase (feature extraction + fine-tuning)
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- **Dataset:** RSNA Pneumonia Detection Challenge (26,684 patients)
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- **Input Size:** 224x224x3
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- **Optimal Threshold:** 0.4376 (Youden's J)
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## Usage
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```python
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