Rethinking domain adaptation for machine learning over clinical language

Building clinical natural language processing (NLP) systems that work on widely varying data is an absolute necessity because of the expense of obtaining new training data. While domain adaptation research can have a positive impact on this problem, the most widely studied paradigms do not take into...

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Detalles Bibliográficos
Autores principales: Laparra, Egoitz, Bethard, Steven, Miller, Timothy A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Perspective
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382626/
https://www.ncbi.nlm.nih.gov/pubmed/32734151
http://dx.doi.org/10.1093/jamiaopen/ooaa010

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382626/
https://www.ncbi.nlm.nih.gov/pubmed/32734151
http://dx.doi.org/10.1093/jamiaopen/ooaa010

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