论文标题
医疗领域的联合学习 - 管道，应用和挑战
Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges
论文作者
论文摘要
联合学习是通过分布在医院，临床研究实验室和移动设备等数据中心的数据集上开发机器学习模型的过程，同时防止数据泄漏。这项调查研究了对医疗保健部门联合学习的先前研究和研究，这些用例和应用程序范围内。我们的调查显示了从业人员在联合学习的主题中应注意的挑战，方法和应用程序。本文旨在列出现有的研究，并列出医疗保健行业联邦学习的可能性。
Federated learning is the process of developing machine learning models over datasets distributed across data centers such as hospitals, clinical research labs, and mobile devices while preventing data leakage. This survey examines previous research and studies on federated learning in the healthcare sector across a range of use cases and applications. Our survey shows what challenges, methods, and applications a practitioner should be aware of in the topic of federated learning. This paper aims to lay out existing research and list the possibilities of federated learning for healthcare industries.
