Transforming nursing with large language models: from concept to practice.

Journal: European journal of cardiovascular nursing
Published Date:

Abstract

Large language models (LLMs) such as ChatGPT have emerged as potential game-changers in nursing, aiding in patient education, diagnostic assistance, treatment recommendations, and administrative task efficiency. While these advancements signal promising strides in healthcare, integrated LLMs are not without challenges, particularly artificial intelligence hallucination and data privacy concerns. Methodologies such as prompt engineering, temperature adjustments, model fine-tuning, and local deployment are proposed to refine the accuracy of LLMs and ensure data security. While LLMs offer transformative potential, it is imperative to acknowledge that they cannot substitute the intricate expertise of human professionals in the clinical field, advocating for a synergistic approach in patient care.

Authors

  • Brigitte Woo
    Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Tom Huynh
    School of Science, Engineering and Technology, RMIT University, Vietnam.
  • Arthur Tang
    School of Science, Engineering and Technology, RMIT University, Viet Nam. Electronic address: arthur.tang@rmit.edu.vn.
  • Nhat Bui
    School of Science, Engineering and Technology, RMIT University, 702 Nguyen Van Linh Blvd., District 7, Ho Chin Minh 756000, Ho Chin Minh City, Vietnam.
  • Giang Nguyen
    Department of English, Hanoi University, Hanoi, Vietnam.
  • Wilson Tam
    Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.