A new study reveals that large language models (LLMs) can lose their initial correct medical diagnoses under pressure, highlighting a gap between medical knowledge and robustness. The proposed solutions, including a lightweight defense mechanism and resilience-oriented fine-tuning, aim to enhance the stability of LLMs in clinical settings.