Metadata-Version: 2.4
Name: matchminer-ai
Version: 0.3.1
Summary: MatchMiner-AI package
Maintainer-email: Sabrina Camp <sabrinay_camp@dfci.harvard.edu>, Ken Kehl <Kenneth_Kehl@dfci.harvard.edu>
License-Expression: CC-BY-NC-ND-4.0
Project-URL: Homepage, https://github.com/dfci/matchminer-ai-inference
Project-URL: Repository, https://github.com/dfci/matchminer-ai-inference
Project-URL: Issues, https://github.com/dfci/matchminer-ai-inference/issues
Keywords: clinical-trials,oncology,trial-matching,natural-language-processing,large-language-models
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Requires-Python: >=3.12
Description-Content-Type: text/markdown
License-File: LICENSE
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Requires-Dist: pandas>=2.3
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Requires-Dist: transformers>=5.8.0
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Dynamic: license-file

# matchminer-ai

## Overview

`matchminer-ai` is a Python package for running the clinical trial matching inference workflow described in [Altreuter et al., MatchMiner-AI: An Open-Source Solution for Cancer Clinical Trial Matching](https://doi.org/10.48550/arXiv.2412.17228). The package provides modular functions for the core MatchMiner-AI workflow: summarizing trials and patient histories, generating embeddings of each, retrieving candidate matches, scoring match quality, and assessing exclusion criteria.

For detailed instructions, please see the
[documentation website](https://dfci.github.io/matchminer-ai-inference/).

> [!WARNING]
> This package is currently pre-v1 and under active development.

## Compute requirements

A GPU is recommended for the clinical trial matching inference workflow. Please see the
[requirements documentation](https://dfci.github.io/matchminer-ai-inference/getting-started/requirements/)
for more information on compute expectations and GPU recommendations.

## Installation

This package requires Python 3.12+.

The package has been tested in Linux environments.

We recommend using [`uv`](https://docs.astral.sh/uv/) to create the Python
environment and install the package:

```shell
uv venv --python 3.12
source .venv/bin/activate
uv pip install matchminer-ai
```

## Quickstart
See the example notebook for a full walkthrough using sample input data:
[example notebook](https://github.com/dfci/matchminer-ai-inference/blob/main/examples/run_examples.ipynb)

## Citation

If you use `matchminer-ai`, please cite:
>Altreuter J, Trukhanov P, Paul MA, Hassett MJ, Riaz IB, Afzal MU, Mohammed AA, Sammons S, Lindsay J, Mallaber E, Klein HR, Gungor G, Galvin M, Deletto M, Van Nostrand SC, Provencher J, Yu J, Tahir N, Wischhusen J, Kozyreva O, Ortiz T, Tuncer H, Masri JE, Malcolm A, Mazor T, Cerami E, Kehl KL. MatchMiner-AI: An Open-Source Solution for Cancer Clinical Trial Matching. *arXiv*. 2026. doi: [10.48550/arXiv.2412.17228](https://doi.org/10.48550/arXiv.2412.17228)

## Contributing

Contributions are welcome! Please follow our
[contribution instructions][contributing] if you are interested in contributing
to this project.

[contributing]: https://dfci.github.io/matchminer-ai-inference/development/contributing/
