Chest Xray Classifier

--- license: mit library_name: transformers pipeline_tag: image-classification base_model: facebook/convnextv2-tiny-22k-224 tags: - chest-xray - convnext - convnextv2 - image-classification - medical - medical-imaging - pneumonia - pytorch - transformers datasets: - keremberke/chest-xray-classification metrics: - accuracy - f1 widget: - src: https://huggingface.co/kiselyovd/chest-xray-classifier/resolve/main/samples/bacterial_pneumonia.png example_title: bacterial_pneumonia - src: https://huggingface.co/kiselyovd/chest-xray-classifier/resolve/main/samples/normal.png example_title: normal - src: https://huggingface.co/kiselyovd/chest-xray-classifier/resolve/main/samples/viral_pneumonia.png example_title: viral_pneumonia model-index: - name: kiselyovd/chest-xray-classifier results: - task: type: image-classification dataset: type: keremberke/chest-xray-classification name: Chest X-Ray Images (Pneumonia) metrics: - type: auroc_macro_ovr value: 0.9752638346619307 - type: accuracy value: 0.9134615384615384 - type: macro_f1 value: 0.9029730638714358 --- # chest-xray-classifier <p align="center"> <img src="hero.jpg" width="100%" alt="chest-xray-classifier - 3-class pneumonia classification" /> </p> A 3-class chest X-ray classifier that distinguishes **bacterial pneumonia**, **normal**, and **viral pneumonia** on pediatric frontal chest radiographs. The main model is a [ConvNeXt-V2-Tiny](https://huggingface.co/facebook/convnextv2-tiny-22k-224) fine-tuned with the `transformers` library; a DINOv2 ViT-S linear probe serves as the baseline. > Medical disclaimer: this model is provided for research and educational purposes only. It is not a medical device and must not be used for clinical diagnosis or treatment decisions. ## Metrics Evaluated on the held-out test split (624 radiographs: 242 bacterial / 234 normal / 148 viral). All values are reported as percentages. | Model | Accuracy | Macro F1 | Macro AUROC (OvR) | |---|---|---|---| | **ConvNeXt-V2-Tiny** (main) | **91.3%** | **90.3%** | **97.5%** | | DINOv2 ViT-S linear probe (baseline) | 85.6% | 84.2% | 94.2% | ### Per-class results (main model) | Class | Precision | Recall | F1 | Support | |---|---|---|---|---| | bacterial_pneumonia | 89.1% | 98.3% | 93.5% | 242 | | normal | 99.5% | 89.7% | 94.4% | 234 | | viral_pneumonia | 83.6% | 82.4% | 83.0% | 148 | | **Macro a...

Source context: 65 downloads · 1 likes · Pipeline image-classification · Library transformers · Repo kiselyovd/chest-xray-classifier