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October 16, 2025Open Access

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

Key Points

Generative large language models demonstrate strengths in open-ended medical tasks, highlighting their potential.
Traditional natural language processing outperforms generative models in information extraction and analysis tasks.
The study analyzed 19,123 studies to compare the effectiveness of these technologies in medical applications.
Ethical use of generative LLMs and NLP is essential as these technologies continue to evolve in the medical field.

Abstract

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.

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

Key Points

Abstract

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