Enhancing Nursing and Elderly Care with Large Language Models: An AI-Driven Framework
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Abstract (arXiv)
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 a dynamic 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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 26 references that are in the map. First posted on arXiv 13 Dec 2024.
Builds on
5 of 26 references.
References · 5
- 2023Improved Baselines with Visual Instruction Tuningcited by 4,418
- 2023A Survey of Large Language Models in Medicine: Progress, Application, and Challengecited by 124
- 2024Language Model Meets Prototypes: Towards Interpretable Text Classification Models through Prototypical Networkscited by 5
- 2024GAProtoNet: A Multi-head Graph Attention-based Prototypical Network for Interpretable Text Classificationcited by 4
- 2023MedNgage: A Dataset for Understanding Engagement in Patient-Nurse Conversationscited by 3
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2 papers.