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| 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..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:1import tensorflow as tf
2from huggingface_hub import hf_hub_download
3# Register your custom classes — see src/train/ in the source repo
4from custom_layers import DeepSet, TransformerBlock, F2Score # noqa: F401
5
6path = hf_hub_download(
7 repo_id="<user-or-org>/<repo-name>",
8 filename="mortality_30day/mort_hypertrial_auc.keras",
9)
10model = tf.keras.models.load_model(path)_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