Upload NRD ICD-10 outcome models

.gitattributes

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+mortality_30day/mort_hypertrial_auc.keras filter=lfs diff=lfs merge=lfs -text
+mortality_30day/mort_icd_only.keras filter=lfs diff=lfs merge=lfs -text
+mortality_30day/mort_no_deepset.keras filter=lfs diff=lfs merge=lfs -text
+mortality_30day/mort_transformer.keras filter=lfs diff=lfs merge=lfs -text
+readmission_30day/readmit_auc_icd_only_final.keras filter=lfs diff=lfs merge=lfs -text
+readmission_30day/readmit_auc_no_deepset.keras filter=lfs diff=lfs merge=lfs -text
+readmission_30day/readmit_auc_with_transformers.keras filter=lfs diff=lfs merge=lfs -text
+readmission_30day/readmit_hypertrial_auc.keras filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+library_name: keras
+tags:
+  - healthcare
+  - icd-10
+  - mortality-prediction
+  - readmission-prediction
+  - deepset
+  - tabular
+---
+
+# NRD ICD-10 outcome models
+
+DeepSet + (optional) Transformer models trained on the National Readmission
+Database (NRD, 2016–2020) to predict two outcomes from up to 40 ICD-10
+diagnosis codes plus demographics (AGE, FEMALE, PAY1, ZIPINC_QRTL).
+
+| Subfolder            | Outcome  | Description                          |
+|----------------------|----------|--------------------------------------|
+| `mortality_30day/`   | `MOR30`  | 30-day post-discharge mortality      |
+| `readmission_30day/` | `REA30`  | 30-day all-cause readmission         |
+
+`encoders/` holds the fitted `LabelEncoder` (ICD-10 → integer IDs) and
+`MinMaxScaler` (AGE) used at training time. Inputs must be encoded with the
+**same** artifacts at inference, or predictions will be meaningless.
+
+## Loading a model
+
+The `.keras` files contain three custom serializable components
+(`DeepSet`, `TransformerBlock`, `F2Score`) that must be importable (and
+registered via `@tf.keras.utils.register_keras_serializable(package="Custom")`)
+before `load_model`:
+
+```python
+import tensorflow as tf
+from huggingface_hub import hf_hub_download
+# Register your custom classes — see src/train/ in the source repo
+from custom_layers import DeepSet, TransformerBlock, F2Score  # noqa: F401
+
+path = hf_hub_download(
+    repo_id="<user-or-org>/<repo-name>",
+    filename="mortality_30day/mort_hypertrial_auc.keras",
+)
+model = tf.keras.models.load_model(path)
+```
+
+## Variants
+
+Within each outcome subfolder, file suffixes denote the architecture:
+
+- `_hypertrial_auc` — best model from the Keras-Tuner search (recommended)
+- `_icd_only` — ICD codes only, no demographics (ablation)
+- `_no_deepset` — flattened ICD input, no DeepSet aggregation (ablation)
+- `_with_transformers` / `_transformer` — DeepSet + TransformerBlocks
+
+## Data restrictions
+
+NRD is a HCUP product distributed under a Data Use Agreement. These weights
+do not contain individual records, but downstream users should be aware of
+the source.

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