Multimodal Federated Learning in Healthcare: a Review

arXiv:2310.09650v2 Announce Type: replace
Abstract: Recent advancements in multimodal machine learning have empowered the development of accurate and robust AI systems in the medical domain, especially within centralized database systems. Simultaneously, Federated Learning (FL) has progressed, providing a decentralized mechanism where data need not be consolidated, thereby enhancing the privacy and security of sensitive healthcare data. The integration of these two concepts supports the ongoing progress of multimodal learning in healthcare while ensuring the security and privacy of patient records …

abstract ai systems arxiv cs.ai cs.lg data database decentralized development domain federated learning healthcare machine machine learning medical multimodal privacy privacy and security review robust security systems type