Adapting Pretrained Language Models for Solving Tabular Prediction Problems in the Electronic Health...
Adapting Pretrained Language Models for Solving Tabular Prediction Problems in the Electronic Health Record
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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We propose an approach for adapting the DeBERTa model for electronic health record (EHR) tasks using domain adaptation. We pretrain a small DeBERTa model on a dataset consisting of MIMIC-III discharge summaries, clinical notes, radiology reports, and PubMed abstracts. We compare this model's performance with a DeBERTa model pre-trained on clinical...
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Adapting Pretrained Language Models for Solving Tabular Prediction Problems in the Electronic Health Record
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TN_cdi_proquest_journals_2791773285
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2791773285
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2331-8422
