Development and Validation of a Deep Learning Model for Detection of Allergic Reactions Using Safety Event Reports Across Hospitals

IMPORTANCE: Although critical to patient safety, health care–related allergic reactions are challenging to identify and monitor. OBJECTIVE: To develop a deep learning model to identify allergic reactions in the free-text narrative of hospital safety reports and evaluate its generalizability, efficie...

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Detalles Bibliográficos
Autores principales: Yang, Jie, Wang, Liqin, Phadke, Neelam A., Wickner, Paige G., Mancini, Christian M., Blumenthal, Kimberly G., Zhou, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2020
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670315/
https://www.ncbi.nlm.nih.gov/pubmed/33196805
http://dx.doi.org/10.1001/jamanetworkopen.2020.22836

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670315/
https://www.ncbi.nlm.nih.gov/pubmed/33196805
http://dx.doi.org/10.1001/jamanetworkopen.2020.22836

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