LLMs in Biomedicine: A study on clinical Named Entity Recognition

arXiv:2404.07376v1 Announce Type: new
Abstract: Large Language Models (LLMs) demonstrate remarkable versatility in various NLP tasks but encounter distinct challenges in biomedicine due to medical language complexities and data scarcity. This paper investigates the application of LLMs in the medical domain by exploring strategies to enhance their performance for the Named-Entity Recognition (NER) task. Specifically, our study reveals the importance of meticulously designed prompts in biomedicine. Strategic selection of in-context examples yields a notable improvement, showcasing ~15-20\% increase in F1 …

abstract application arxiv biomedicine challenges clinical complexities cs.cl data domain language language models large language large language models llms medical nlp paper performance recognition strategies study tasks type