The survey of large language models (LLMs) reveals their expanding role across various domains, notably healthcare. Zhao et al. (2023) explore the capabilities of LLMs, while Achiam et al. (2023) highlight advancements in recent models like GPT-4. Emerging multimodal models, including Gemini by Team G (2023), raise questions on their efficacy in diverse applications. Various studies explore LLMs in education, biomedicine (Thirunavukarasu et al., 2023; Gao et al., 2024), and precision oncology (Singhal et al., 2024). Key findings indicate their potential to optimize clinical workflows, enhance decision-making, and improve patient engagement, yet challenges such as bias (Ferrara, 2023) and security risks (Yao et al., 2024) persist. Furthermore, advancements in health informatics and decision support systems underscore the need for responsible AI integration in clinical practices (Kim et al., 2024). Harnessing LLMs could transform healthcare but will require ongoing scrutiny regarding ethical implications and accuracy.
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