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

作者：Anne de Hond, Tuur Leeuwenberg, Richard Bartels, Marieke van Buchem, Ilse Kant, Karel G.M. Moons, Maarten van Smeden · 发表于：The Lancet Digital Health · 年份：2024 · DOI：10.1016/s2589-7500(24)00111-0 · 被引用次数：52 · 研究领域：Topic Modeling、Biomedical Text Mining and Ontologies、Machine Learning in Healthcare

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.