STAN: spatio-temporal attention network for pandemic prediction using real-world evidence

OBJECTIVE: We aim to develop a hybrid model for earlier and more accurate predictions for the number of infected cases in pandemics by (1) using patients’ claims data from different counties and states that capture local disease status and medical resource utilization; (2) utilizing demographic simi...

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Detalles Bibliográficos
Autores principales: Gao, Junyi, Sharma, Rakshith, Qian, Cheng, Glass, Lucas M, Spaeder, Jeffrey, Romberg, Justin, Sun, Jimeng, Xiao, Cao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7928935/
https://www.ncbi.nlm.nih.gov/pubmed/33486527
http://dx.doi.org/10.1093/jamia/ocaa322

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7928935/
https://www.ncbi.nlm.nih.gov/pubmed/33486527
http://dx.doi.org/10.1093/jamia/ocaa322

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