Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19

Machine learning (ML) models require large datasets which may be siloed across different healthcare institutions. Using federated learning, a ML technique that avoids locally aggregating raw clinical data across multiple institutions, we predict mortality within seven days in hospitalized COVID-19 p...

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Detalhes bibliográficos
Publicado no:medRxiv
Main Authors: Vaid, Akhil, Jaladanki, Suraj K, Xu, Jie, Teng, Shelly, Kumar, Arvind, Lee, Samuel, Somani, Sulaiman, Paranjpe, Ishan, De Freitas, Jessica K, Wanyan, Tingyi, Johnson, Kipp W, Bicak, Mesude, Klang, Eyal, Kwon, Young Joon, Costa, Anthony, Zhao, Shan, Miotto, Riccardo, Charney, Alexander W, Böttinger, Erwin, Fayad, Zahi A, Nadkarni, Girish N, Wang, Fei, Glicksberg, Benjamin S
Formato: Artigo
Idioma:Inglês
Publicado em: Cold Spring Harbor Laboratory 2020
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7430624/
https://ncbi.nlm.nih.gov/pubmed/32817979
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1101/2020.08.11.20172809
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