Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach

BACKGROUND: Machine learning models require large datasets that may be siloed across different health care institutions. Machine learning studies that focus on COVID-19 have been limited to single-hospital data, which limits model generalizability. OBJECTIVE: We aimed to use federated learning, a ma...

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Detalles Bibliográficos
Autores principales: 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: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842859/
https://www.ncbi.nlm.nih.gov/pubmed/33400679
http://dx.doi.org/10.2196/24207

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842859/
https://www.ncbi.nlm.nih.gov/pubmed/33400679
http://dx.doi.org/10.2196/24207

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