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auto-ehrmonize-flowsheet

Clinical flowsheet label harmonization using sentence embeddings and vector search.

Install

pip install auto-ehrmonize-flowsheet

One-time setup

Download the vector database (ChromaDB + HDF5 value embeddings) from HuggingFace into ~/.auto_ehrmonize_flowsheet/:

ehrmonize setup --token <HF_TOKEN> --repo-id <user/repo>

Alternatively, set HUGGING_FACE_KEY and HF_REPO_ID as environment variables (or in a .env file in your working directory) and just run ehrmonize setup.

Quick start (Python)

from auto_ehrmonize_flowsheet import AutoEHRmonizeFlowsheet

harmonizer = AutoEHRmonizeFlowsheet("data/test_data.csv")
results = harmonizer.harmonize("Heart Rate")
print(results)

CLI

# Look up a single label
ehrmonize lookup "Heart Rate" --data data/test_data.csv

# With options
ehrmonize lookup "Heart Rate" --data data/test_data.csv --source mimic --threshold 0.6 --top-k 5

# List unique labels in your dataset
ehrmonize labels --data data/test_data.csv

License

MIT

Metadata

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