Recent advances in defending the privacy attacks of large language models for healthcare applications: a concise review
Tiehang Duan
Large language models (LLMs) are increasingly adopted across healthcare applications, including clinical decision support and medical documentation systems. However, their deployment in medical settings raises significant privacy and security concerns due to the sensitivity of protected health information and stringent regulatory requirements. Recent studies have shown that LLM-based medical applications can cause medical data leakage through related API usages. This raises ethical concerns and