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The inherent sensitivity of patient data introduces a complex challenge in the field of health care. Through the use of decentralized algorithms in federated learning, the process of data aggregation is rendered unnecessary. This paper presents a survey of federated learning, with an emphasis on its use in healthcare and ophthalmology. We address the accompanying