Privacy-preserving AI in healthcare: a comprehensive survey of techniques and challenges
This study aims to guide researchers and practitioners in designing secure, efficient, and privacy-preserving AI systems for healthcare by proposing a structured classification of privacy-preserving methods into four main categories: cryptographic approaches, decentralized learning methods, perturbation-based techniques, and hybrid models.