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**Cohort:** 9,137 ED-anchored studies, 80/10/10 patient-level temporal split, test set n = 1,075
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**Backbone:** DenseNet-121 pretrained on 14-label CheXpert task, fine-tuned for binary pneumonia
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**Backbone:** DenseNet-121 pretrained on the multilabel CheXpert-style task using 41,214 non-ED MIMIC-CXR-JPG studies, then fine-tuned for binary pneumonia
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multimodal-pneumonia make all
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```
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Trained weights (~800 MB–1.2 GB per checkpoint) are not in the repository. Contact the author for access.
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Trained weights (~800 MB–1.2 GB per checkpoint) are not redistributed under the PhysioNet Data Use Agreement. To obtain weights, complete PhysioNet credentialing and re-run `make all` after configuring `configs/paths.local.yaml`.
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## Dashboard
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```bash
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streamlit run streamlit_app.py
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```
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The dashboard reads pre-computed metrics from `artifacts/evaluation/` and runs without MIMIC access for browsing results, calibration plots, bootstrap comparisons, and Grad-CAM overlays.
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---
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## Data compliance
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Uses MIMIC-CXR-JPG v2.1.0, MIMIC-IV, and MIMIC-IV-ED under the PhysioNet Credentialed Health Data License. No patient-level data is committed to this repository. Reproducing results requires completing PhysioNet credentialing at [physionet.org](https://physionet.org).
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Uses MIMIC-CXR-JPG v2.1.0, MIMIC-IV v2.2, and MIMIC-IV-ED v2.2 under the PhysioNet Credentialed Health Data License. No patient-level data is committed to this repository. Reproducing results requires completing PhysioNet credentialing at [physionet.org](https://physionet.org).
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