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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Detaylı Bibliyografya
Yayımlandı:medRxiv
Asıl Yazarlar: 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
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: Cold Spring Harbor Laboratory 2020
Konular:
Article
Online Erişim: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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