Poster
in
Workshop: Workshop on Learning from Time Series for Health
Medical Event Data Standard (MEDS): Facilitating Machine Learning for Health
Bert Arnrich · Edward Choi · Jason Fries · Matthew McDermott · Jungwoo Oh · Tom Pollard · Nigam Shah · Ethan Steinberg · Michael Wornow · Robin van de Water
Keywords: [ Healthcare ] [ foundation models ] [ benchmarking ] [ machine learning ]
We introduce the Medical Event Data Standard (MEDS), a lightweight schema for enabling machine learning over electronic health record (EHR) data. Unlike common data models and data interoperability formats, MEDS is a minimal standard designed for maximum interoperability across datasets, existing tools, and model architectures. By providing a simple standardization layer between datasets and model-specific code, MEDS will enable more reproducible, robust, computationally performant, and collaborative machine learning research using EHR data. We highlight several existing MEDS integrations with models, datasets, and tools, and invite the community for further development and adoption.