Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis

Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By co...

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Detalles Bibliográficos
Autores principales: Wagner, Tyler, Shweta, FNU, Murugadoss, Karthik, Awasthi, Samir, Venkatakrishnan, AJ, Bade, Sairam, Puranik, Arjun, Kang, Martin, Pickering, Brian W, O'Horo, John C, Bauer, Philippe R, Razonable, Raymund R, Vergidis, Paschalis, Temesgen, Zelalem, Rizza, Stacey, Mahmood, Maryam, Wilson, Walter R, Challener, Douglas, Anand, Praveen, Liebers, Matt, Doctor, Zainab, Silvert, Eli, Solomon, Hugo, Anand, Akash, Barve, Rakesh, Gores, Gregory, Williams, Amy W, Morice, William G, Halamka, John, Badley, Andrew, Soundararajan, Venky
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2020
Materias:
Human Biology and Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7410498/
https://www.ncbi.nlm.nih.gov/pubmed/32633720
http://dx.doi.org/10.7554/eLife.58227

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7410498/
https://www.ncbi.nlm.nih.gov/pubmed/32633720
http://dx.doi.org/10.7554/eLife.58227

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