Nov. 5, 2023, 6:44 a.m. | Michael Wornow, Rahul Thapa, Ethan Steinberg, Jason A. Fries, Nigam H. Shah

cs.LG updates on arXiv.org arxiv.org

While the general machine learning (ML) community has benefited from public
datasets, tasks, and models, the progress of ML in healthcare has been hampered
by a lack of such shared assets. The success of foundation models creates new
challenges for healthcare ML by requiring access to shared pretrained models to
validate performance benefits. We help address these challenges through three
contributions. First, we publish a new dataset, EHRSHOT, which contains
deidentified structured data from the electronic health records (EHRs) of …

arxiv benchmark challenges community datasets ehr evaluation few-shot foundation general healthcare machine machine learning progress public success tasks

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