The widespread uptake of the Internet of Medical Things (IoMT) has transformed healthcare by facilitating real-time monitoring and data-driven decision-making, but maintaining data privacy and security is a vital challenge because data breaches and unauthorized access are on the rise. Differential Privacy (DP) and Federated Meta-Learning (FML) are being seen as promising candidates to tackle these issues with the model performance maintained, wherein DP adds noise to sensitive data in a controlled manner for rigorous privacy assurance, and FML allows for personalized learning across distributed IoMT devices without the need for patient data centralization. This survey delves into the combina... More >