Adapting and evaluating a deep learning language model for clinical why-question answering

OBJECTIVES: To adapt and evaluate a deep learning language model for answering why-questions based on patient-specific clinical text. MATERIALS AND METHODS: Bidirectional encoder representations from transformers (BERT) models were trained with varying data sources to perform SQuAD 2.0 style why-que...

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Detalles Bibliográficos
Autores principales: Wen, Andrew, Elwazir, Mohamed Y, Moon, Sungrim, Fan, Jungwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Brief Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309262/
https://www.ncbi.nlm.nih.gov/pubmed/32607483
http://dx.doi.org/10.1093/jamiaopen/ooz072

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309262/
https://www.ncbi.nlm.nih.gov/pubmed/32607483
http://dx.doi.org/10.1093/jamiaopen/ooz072

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