Nature Reviews Safety and Security Risks of Large Language Models in Healthcare

A high-profile Nature study provides a comprehensive review of safety and security risks specifically associated with deploying large language models in healthcare settings. The paper examines failure modes including hallucination, prompt injection, adversarial inputs, and data privacy vulnerabilities as they manifest in clinical contexts. Healthcare represents one of the highest-stakes deployment environments for LLMs, where errors carry direct patient risk — making this review particularly relevant for teams building in the medical AI space. The study also outlines mitigation strategies and evaluation frameworks that developers and health system implementers can use to assess LLM safety before deployment. For the broader AI developer community, the taxonomy of risks outlined here translates usefully to other high-stakes domains beyond healthcare.