Decentralised federated learning for hospital networks with application to covid-19 detection

HIGHLIGHTS

  • who: ALESSANDRO GIUSEPPI and collaborators from the Department of Computer, Control, and Management Engineering "Antonio Ruberti" (DIAG), University of Rome Sapienza, Via Ariosto, Rome, Italy have published the research work: Decentralised Federated Learning for Hospital Networks with application to COVID-19 Detection, in the Journal: (JOURNAL)
  • what: In this direction, this work proposes a scheme that relies on consensus theory, as introduced in the previous work . The work aims at predicting patients mortality from their EHRs by means of a FL method called Federated-Autonomous Deep Learning (FADL), whose main novelty is that part of . . .

     

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