Generation and evaluation of artificial mental health records for Natural Language Processing

A serious obstacle to the development of Natural Language Processing (NLP) methods in the clinical domain is the accessibility of textual data. The mental health domain is particularly challenging, partly because clinical documentation relies heavily on free text that is difficult to de-identify com...

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Detalles Bibliográficos
Autores principales: Ive, Julia, Viani, Natalia, Kam, Joyce, Yin, Lucia, Verma, Somain, Puntis, Stephen, Cardinal, Rudolf N., Roberts, Angus, Stewart, Robert, Velupillai, Sumithra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224173/
https://www.ncbi.nlm.nih.gov/pubmed/32435697
http://dx.doi.org/10.1038/s41746-020-0267-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224173/
https://www.ncbi.nlm.nih.gov/pubmed/32435697
http://dx.doi.org/10.1038/s41746-020-0267-x

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