Clinical flowsheet label harmonization using sentence embeddings and vector search.
Project description
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
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