Rethinking Evaluation of Large Language Models in Healthcare

Evaluating artificial intelligence (“AI”) in healthcare, particularly large language models (“LLMs”), requires a fundamental shift from conventional testing methods to comprehensive frameworks that assess real-world clinical impact. While AI systems demonstrate impressive performance in controlled research settings, their effectiveness often diminishes in actual clinical environments, highlighting a critical gap between laboratory evaluation and practical deployment. Drawing from measure