| --- |
| language: en |
| license: cc-by-4.0 |
| tags: |
| - image-classification |
| - medical-imaging |
| - chest-xray |
| - pneumonia |
| - efficientnet |
| - gradcam |
| --- |
| |
| # Pneumonia Classification Model (EfficientNet-B0) |
|
|
| Binary classifier for chest X-ray images: **Pneumonia** vs **Normal**. |
|
|
| ## Architecture |
| - **Model**: EfficientNet-B0 (timm) — 4.0M parameters |
| - **Input**: 224×224 RGB (grayscale CXR → 3-channel) |
| - **Pretraining**: ImageNet |
| - **Head**: 2-class linear classifier |
|
|
| ## Dataset |
| - **Source**: [hf-vision/chest-xray-pneumonia](https://huggingface.co/datasets/hf-vision/chest-xray-pneumonia) |
| - **Splits**: Train (5,216) | Validation (16) | Test (624) |
| - **Class imbalance**: ~1:2.9 (Normal:Pneumonia in train) |
|
|
| ## Training Recipe |
| - **Reproducibility**: Fixed seed = 42, deterministic mode |
| - **Augmentation**: RandomHorizontalFlip, RandomRotation(15°), ColorJitter(brightness/contrast 0.05) |
| - **Normalization**: ImageNet stats |
| - **Loss**: Weighted CrossEntropy (inverse class frequency) |
| - **Sampler**: WeightedRandomSampler to balance batches |
| - **Optimizer**: AdamW (lr=1e-4, weight_decay=1e-4) |
| - **Epochs**: 5 (stratified 200+200 subset for balanced training) |
| |
| ## Test Performance |
| | Metric | Score | |
| |--------|-------| |
| | Accuracy | **0.8125** | |
| | Precision (Pneumonia) | **0.7910** | |
| | Recall (Pneumonia) | **0.9513** | |
| | F1-Score | **0.8638** | |
| | ROC-AUC | **0.9037** | |
| |
| ## Explainability |
| Grad-CAM heatmaps are included in `gradcam/` to visualize regions influencing predictions. |
| |
| ## Files |
| - `model.pt` — Trained model checkpoint (state_dict + config + results) |
| - `results.json` — Detailed metrics and class distribution |
| - `cm.png` — Confusion matrix |
| - `roc.png` — ROC curve |
| - `gradcam/*.png` — Grad-CAM overlays |
|
|
| ## Limitations |
| - Trained on a small stratified subset (400 images) due to compute constraints; full-dataset training would further improve generalization. |
| - Validation set is very small (16 images); results may have high variance. |
| - No clinical validation performed; intended for research/educational use only. |
| - Class imbalance in the original dataset was addressed via sampling but may not fully represent real-world prevalence. |
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