Recent research highlights significant advancements and challenges in utilizing large language models (LLMs) in healthcare. Notably, AlphaFold demonstrates high accuracy in protein structure predictions, paving the way for innovations in biomedicine (Jumper et al., 2021). However, studies emphasize the need for cautious navigation of LLM benefits and pitfalls within clinical settings (Ray, 2024). Reviews have assessed the landscape and effectiveness of LLMs in patient care, revealing both their utility and potential ethical concerns (Park et al., 2024; Ong et al., 2024). Furthermore, systematic evaluations indicate that while LLMs can generate informative patient materials, issues such as bias and reliability persist (Ullah et al., 2024; Saeidnia et al., 2024). As LLM applications continue to expand, future research must focus on validating their effectiveness and addressing regulatory challenges to enhance safety and efficacy in healthcare environments.
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