Multimodal Federated Learning for Secure and Accurate Healthcare AI
Published in arXiv preprint, 2023
This paper reviews the role of multimodal federated learning in healthcare, highlighting its potential to combine diverse medical data while preserving patient privacy. It surveys state-of-the-art approaches, identifies current challenges and limitations, and outlines future directions for advancing secure and effective healthcare AI.
Citation: Thrasher, J., Devkota, A., Siwakotai, P., Chivukula, R., Poudel, P., Hu, C., Bhattarai, B. and Gyawali, P., 2023. Multimodal federated learning in healthcare: a review. arXiv preprint arXiv:2310.09650.
Citation: Thrasher, J., Devkota, A., Siwakotai, P., Chivukula, R., Poudel, P., Hu, C., Bhattarai, B. and Gyawali, P., 2023. Multimodal federated learning in healthcare: a review. arXiv preprint arXiv:2310.09650.
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