PyM-FL: A Prototyping Approach for Multimodal Federated Learning

Federated learning has demonstrated applicability in extracting insights from homogeneous data across clients.However, in real-world scenarios, the prevalence of multimodal data is on the rise, driven by the complex nature of industrial processes, which brings a new challenge-training heterogeneous models via multimodal data in federated learning.This paper proposes a novel federated learning approach called PyM-FL to tackle this challenge.The efficacy of PyM-FL is assessed through an experiment focused on the diagnosis of mild cognitive impairment.