This paper is in the following e-collection/theme issue:

Theme Issue: Medical Informatics and COVID-19 (107) JMIR Theme Issue: COVID-19 Special Issue (2452) Machine Learning (1465) Secondary Use of Clinical Data for Research and Surveillance (366) Infectious Diseases (non-STD/STI) (1575) Innovative Methods in Public Health and Surveillance (332) Outbreak and Pandemic Preparedness and Management (1727) Surveillance Systems (462)

Published on in Vol 9, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24207, first published .
Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach

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

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

Authors of this article:

Akhil Vaid1, 2 Author Orcid Image ;   Suraj K Jaladanki1, 2 Author Orcid Image ;   Jie Xu3 Author Orcid Image ;   Shelly Teng1, 2 Author Orcid Image ;   Arvind Kumar1, 2 Author Orcid Image ;   Samuel Lee1, 2 Author Orcid Image ;   Sulaiman Somani1, 2 Author Orcid Image ;   Ishan Paranjpe1, 2 Author Orcid Image ;   Jessica K De Freitas1, 2, 4 Author Orcid Image ;   Tingyi Wanyan1, 5, 6 Author Orcid Image ;   Kipp W Johnson1, 2 Author Orcid Image ;   Mesude Bicak1, 2, 4 Author Orcid Image ;   Eyal Klang7 Author Orcid Image ;   Young Joon Kwon8 Author Orcid Image ;   Anthony Costa8 Author Orcid Image ;   Shan Zhao1, 9 Author Orcid Image ;   Riccardo Miotto1, 4 Author Orcid Image ;   Alexander W Charney2, 4, 10, 11 Author Orcid Image ;   Erwin Böttinger1, 2, 12 Author Orcid Image ;   Zahi A Fayad13, 14 Author Orcid Image ;   Girish N Nadkarni1, 2, 15, 16 Author Orcid Image ;   Fei Wang3 Author Orcid Image ;   Benjamin S Glicksberg1, 2, 4 Author Orcid Image
Article Authors Cited by (115) Tweetations (18) Metrics

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