Improving ascertainment of suicidal ideation and suicide attempt with natural language processing

Methods relying on diagnostic codes to identify suicidal ideation and suicide attempt in Electronic Health Records (EHRs) at scale are suboptimal because suicide-related outcomes are heavily under-coded. We propose to improve the ascertainment of suicidal outcomes using natural language processing (...

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Detalles Bibliográficos
Autores principales: Bejan, Cosmin A., Ripperger, Michael, Wilimitis, Drew, Ahmed, Ryan, Kang, JooEun, Robinson, Katelyn, Morley, Theodore J., Ruderfer, Douglas M., Walsh, Colin G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9452591/
https://www.ncbi.nlm.nih.gov/pubmed/36071081
http://dx.doi.org/10.1038/s41598-022-19358-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9452591/
https://www.ncbi.nlm.nih.gov/pubmed/36071081
http://dx.doi.org/10.1038/s41598-022-19358-3

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