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

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.

Ähnliche Arbeiten