Natural language processing-driven state machines to extract social factors from unstructured clinical documentation

OBJECTIVE: This study sought to create natural language processing algorithms to extract the presence of social factors from clinical text in 3 areas: (1) housing, (2) financial, and (3) unemployment. For generalizability, finalized models were validated on data from a separate health system for gen...

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Detalles Bibliográficos
Autores principales: Allen, Katie S, Hood, Dan R, Cummins, Jonathan, Kasturi, Suranga, Mendonca, Eneida A, Vest, Joshua R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10112959/
https://www.ncbi.nlm.nih.gov/pubmed/37081945
http://dx.doi.org/10.1093/jamiaopen/ooad024

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10112959/
https://www.ncbi.nlm.nih.gov/pubmed/37081945
http://dx.doi.org/10.1093/jamiaopen/ooad024

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