A comparative study of pretrained language models for long clinical text.
Objective: Clinical knowledge-enriched transformer models (eg, ClinicalBERT) have state-of-the-art results on clinical natural language processing (NLP) tasks. One of the core limitations of these transformer models is the substantial memory consumption due to their full self-attention mechanism, wh...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 30; no. 2; pp. 340 - 348 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Oxford University Press / USA
Feb2023
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| Acceso en línea: | Ver este registro en EBSCOhost |