Federated learning is a cooperative learning approach that has emerged as an effective way to address privacy concerns. Here, we present a protocol for training MERGE: a federated multi -input neural network (NN) for COVID-19 prognosis. We describe steps for collecting and preprocessing datasets. We then detail the process of training a multi -input NN. This protocol can be adapted for use with datasets containing both image- and table -based input sources. For complete details on the use and execution of this protocol, please refer to Casella et al.1

Protocol for training MERGE: A federated multi-input neural network for COVID-19 prognosis

Riviera, Walter;Menegaz, Gloria
2024-01-01

Abstract

Federated learning is a cooperative learning approach that has emerged as an effective way to address privacy concerns. Here, we present a protocol for training MERGE: a federated multi -input neural network (NN) for COVID-19 prognosis. We describe steps for collecting and preprocessing datasets. We then detail the process of training a multi -input NN. This protocol can be adapted for use with datasets containing both image- and table -based input sources. For complete details on the use and execution of this protocol, please refer to Casella et al.1
2024
Bioinformatics
Clinical Protocol
Computer sciences
Health Sciences
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1145068
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