The current status and prospects of large language models in medical application and research

With the rapid advancement of technology, particularly in artificial intelligence (AI) and natural language processing (NLP), Large Language Models (LLMs) bring significant opportunities for further development in the medical field. But at the same time, it also faces some challenges in precision treatment, personalized patient care, massive data management, and complex clinical decision-making. This paper delves into these issues, offering an exhaustive review of the current applications and research status of LLMs in the medical field. We investigate the potential of LLMs in driving medical technology innovation, facilitating personalized DNA-based treatments, advancing digital healthcare, and in the simulation diagnostics of multidimensional diseases and genetics. Moreover, the study highlights critical challenges confronting LLMs, such as data privacy and security, model interpretability, data scarcity, model generalization capabilities, and the risks associated with over-reliance and misuse. Our review aims to provide an in-depth understanding of LLMs’ current state, potential, and advantages in medicine, ultimately contributing novel insights and solutions for the future progression of healthcare.