COLING 2025main2 citations

Enhancing Nursing and Elderly Care with Large Language Models: An AI-Driven Framework

Qiao Sun, Jiexin Xie, Nanyang Ye, Qinying Gu, Shijie Guo

Abstract

This paper explores the application of large language models (LLMs) in nursing and elderly care, focusing on AI-driven patient monitoring and interaction. We introduce a novel Chinese nursing dataset and implement incremental pre-training (IPT) and supervised fine-tuning (SFT) techniques to enhance LLM performance in specialized tasks. Using LangChain, we develop an interactable nursing assistant capable of real-time care and personalized interventions. Experimental results demonstrate significant improvements, paving the way for AI-driven solutions to meet the growing demands of healthcare in aging populations.

BibTeX
@inproceedings{sun-etal-2025-enhancing,
    title = "Enhancing Nursing and Elderly Care with Large Language Models: An {AI}-Driven Framework",
    author = "Sun, Qiao  and
      Xie, Jiexin  and
      Ye, Nanyang  and
      Gu, Qinying  and
      Guo, Shijie",
    editor = "Rambow, Owen  and
      Wanner, Leo  and
      Apidianaki, Marianna  and
      Al-Khalifa, Hend  and
      Eugenio, Barbara Di  and
      Schockaert, Steven",
    booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
    month = jan,
    year = "2025",
    address = "Abu Dhabi, UAE",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.coling-main.673/",
    pages = "10083--10090"
}
Enhancing Nursing and Elderly Care with Large Language Models: An AI-Driven Framework · COLING 2025