The Evolving Landscape of Generative Large Language Models and Traditional Natural Language Processing in Medicine

Yang, Rui, Li, Huitao, Wong, Matthew Yu Heng, Ke, Yuhe, Li, Xin, Yu, Kunyu, Liao, Jingchi, Liew, Jonathan Chong Kai, Nair, Sabarinath Vinod, Ong, Jasmine Chiat Ling, Li, Irene, Teodoro, Douglas, Hong, Chuan, Ting, Daniel Shu Wei, Liu, Nan

arXiv.org Artificial Intelligence 

Natural language processing (NLP) has been traditionally applied to medicine, and generative large language models (LLMs) have become prominent recently. However, the differences between them across different medical tasks remain underexplored. We analyzed 19,123 studies, finding that generative LLMs demonstrate advantages in open-ended tasks, while traditional NLP dominates in information extraction and analysis tasks. As these technologies advance, ethical use of them is essential to ensure their potential in medical applications.

Duplicate Docs Excel Report

Title
None found

Similar Docs  Excel Report  more

TitleSimilaritySource
None found