From text to treatment: the crucial role of validation for generative large language models in health care

Abstract

Generative large language models (LLMs) have made incredible progress and are speculated to become the next big revolution in health care. Researchers have described several compelling uses for LLMs in health care, including the automatic generation of clinical information letters1 and chatbots answering patient questions.2–4 Thorough validation of developed LLMs is of the utmost importance to their safe and effective application in health-care practice, because incomplete LLM outputs or unchecked LLM hallucinations can be harmful to patient care.

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