Data heterogeneity in federated learning with Electronic Health Records: Case studies of risk prediction for acute kidney injury and sepsis diseases in critical care

• Suraj Rajendran,

  Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliation Tri-Institutional Computational Biology & Medicine Program, Cornell University, New York, New York, United States of America

  https://orcid.org/0000-0002-8149-0157

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• Zhenxing Xu,

  Roles Data curation, Investigation, Supervision, Validation, Writing – original draft, Writing – review & editing

  Affiliation Division of Health Informatics, Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States of America

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• Weishen Pan,

  Roles Investigation, Writing – review & editing

  Affiliation Division of Health Informatics, Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States of America

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• Arnab Ghosh,

  Roles Writing – review & editing

  Affiliation Departments of Medicine, Weill Cornell Medical College, Cornell University, New York, New York, United States of America

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• Fei Wang

  Roles Conceptualization, Funding acquisition, Project administration, Supervision, Writing – review & editing

  * E-mail: few2001@med.cornell.edu

  Affiliation Division of Health Informatics, Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States of America

  https://orcid.org/0000-0001-9459-9461

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