Padé approximant meets federated learning: A nearly lossless, one-shot algorithm for evidence synthesis in distributed research networks with rare outcomes.

Abstract

Authors

• Qiong Wu
  Key Laboratory of Flexible Electronics (KLOFE) and Institute of Advanced Materials (IAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211816, P. R. China.
• Martijn J Schuemie
  Janssen Research and Development, Raritan, NJ, USA.
• Marc A Suchard
  Department of Biomathematics, UCLA School of Medicine, CA, USA.
• Patrick Ryan
  Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
• George M Hripcsak
  Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States of America; Medical Informatics Services, New York-Presbyterian Hospital, New York, NY, United States of America.
• Charles A Rohde
  Department of Biostatistics, Johns Hopkins University, Baltimore, MD, United States of America.
• Yong Chen
  Department of Urology, Chongqing University Fuling Hospital, Chongqing, China.

Keywords

External Resources