MEDS-Transforms

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Authors: Matthew McDermott, Oufattole, Nassim Oufattole, Robin P. van de Water, Patrick Rockenschaub, Ryan King, Simon A. Lee, Chao Pang
Cited by: 0

Abstract

MEDS-Transforms is a Python package for assembling complex data pre-processing workflows over MEDS datasets. To do this, you define a pipeline as a series of stages, each with its own arguments, then run the pipeline over your dataset. This allows the community to curate a library of shared stages for common operations, such as filtering, normalization, outlier detection, and more, which can be used to build novel pipelines for diverse use cases. Learn more below to see how MEDS-Transforms can help you build your data pipelines!

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
5 August 2026