2025 Volume 43 Issue 2 Pages 40-45
This paper discusses the application of artificial intelligence (AI) in the medical domain, with a particular focus on large language models (LLMs) and generative AI. As AI technologies have advanced, the field has seen a shift from traditional statistical models to deep learning approaches. In natural language processing (NLP), models such as BERT and LLMs have come to play a central role. These developments have enabled the simplification of previously complex tasks in medicine, leading to increased efficiency in clinical workflows. Specifically, automation using LLMs is progressing in areas such as routine patient interactions (e.g., obtaining informed consent and cancer consultations) and medical document generation. Furthermore, LLMs are increasingly being employed in the extraction of adverse drug events and the construction of clinical record databases, facilitating the implementation of systems that were previously considered difficult to realize. These advancements are expected to reduce the burden on NLP researchers and accelerate the adoption of AI technologies in clinical settings. This paper provides an overview of how LLMs are transforming the medical field, explores their societal impact, and discusses future prospects.
