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

Rui Yang, Huitao Li, Matthew Yu Heng Wong, Yuhe Ke, Xin Li +10 more
5/15/2025
cs.CLcs.AI

No confident code implementation found for this paper. 2 possible matches can be shown below.

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

A Survey on Large Language Models from General Purpose to Medical Applications: Datasets, Methodologies, and Evaluations

89% match1 repo42024

Benchmarking large language models for biomedical natural language processing applications and recommendations

89% match1 repo182023

A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicine

89% match2024

Large Language Models for Medicine: A Survey

89% match2024

Natural Language Generation in Healthcare: A Review of Methods and Applications

88% match2025

Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data

88% match2024

Cite this paper

@article{yang2025evolving,
  title  = {The Evolving Landscape of Generative Large Language Models and Traditional Natural Language Processing in Medicine},
  author = {Rui Yang and Huitao Li and Matthew Yu Heng Wong and Yuhe Ke and Xin Li and Kunyu Yu and Jingchi Liao and Jonathan Chong Kai Liew and Sabarinath Vinod Nair and Jasmine Chiat Ling Ong and Irene Li and Douglas Teodoro and Chuan Hong and Daniel Shu Wei Ting and Nan Liu},
  year   = {2025},
  eprint = {2505.10261},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2505.10261v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2505.10261.svg)](https://codeofpaper.com/paper/2505.10261)

Discussion