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Components

Most users only need meddeid to de-identify text. Add another component when you need to prepare data, review annotations, train a model, or evaluate a system.

Click a component name to open its GitHub repository. That repository contains the detailed installation instructions, configuration, release notes, and development documentation for the component.

Run de-identification

meddeid

Use this for ordinary de-identification: process one note or a batch through the CLI or Python API, or run the optional HTTP service.

PyPI: pip install meddeid

Prepare, review, train, and evaluate

These components correspond to optional workflow steps. Use only the ones your project needs.

meddeid-data

Use this to import source files into a MedDeID project, create stable document identifiers and splits, validate data, or generate synthetic data.

PyPI: pip install 'meddeid-data[parquet]'

meddeid-annotate

Use this local browser application to review identifiers in an assigned JSONL file and save completed primary annotations.

GHCR: docker pull ghcr.io/stighellemans/meddeid-annotate:0.2.0

meddeid-curate

Use this only when multiple reviewers annotated the same documents and a curator needs to resolve their differences.

GHCR: docker pull ghcr.io/stighellemans/meddeid-curate:0.2.0

meddeid-subannotate

Use this only when a benchmark needs detailed character-level labels inside reviewed identifiers. Ordinary annotation and training do not require it.

GHCR: docker pull ghcr.io/stighellemans/meddeid-subannotate:0.2.0

meddeid-training

Use this to train or adapt a model from reviewed data, select and refit a checkpoint, and export a model bundle for inference.

PyPI: pip install 'meddeid-training[train,plots]'

meddeid-eval

Use this to score predictions against reviewed test data, compare systems, and create performance and stability analyses.

PyPI: pip install 'meddeid-eval[plots]'

Shared foundations

You normally do not choose these packages directly: meddeid and the workflow tools install the capabilities they need. They are most relevant when you are integrating with the data contract, developing language behavior, or contributing to the suite.

meddeid-core

Defines the shared record schema, label taxonomy, normalization, stable identifiers, and offset validation used by all components.

PyPI: pip install meddeid-core

meddeid-language-nl

Provides Dutch parsing, rendering, resources, and post-processing for nl-BE and nl-NL.

PyPI: pip install meddeid-language-nl

npm: npm install @meddeid/language-nl@0.2.1

meddeid-language-en

Provides English parsing, rendering, resources, and locale-specific post-processing for en-GB and en-US.

PyPI: pip install meddeid-language-en

npm: npm install @meddeid/language-en@0.2.1

Other useful destinations

These are not additional components to install. They are places you may need while trying MedDeID, selecting an artifact, or contributing to a coordinated release.

Destination Use it when you want to…
MedDeID documentation Choose a workflow and understand how components work together
Non-clinical demo Try the interface with synthetic or otherwise non-sensitive text
Hugging Face collection Find published models, datasets, benchmark data, and their artifact cards
meddeid-suite Coordinate versions and verify a release across all components

The suite's publication/ and internal/ directories are maintainer records, not reader-facing products. External comparison systems are also not MedDeID components; run them independently and convert their predictions before using meddeid-eval.

Documentation ownership

This site helps you choose a component and follow workflows that cross repository boundaries. Component repositories are authoritative for their API, CLI options, configuration, tests, and release notes. Hugging Face artifact cards are authoritative for model and dataset contents, limitations, licences, and immutable revisions.