Transforming nursing with large language models: from concept to practice

被引:7
|
作者
Woo, Brigitte [1 ]
Huynh, Tom [2 ]
Tang, Arthur [2 ]
Bui, Nhat [2 ]
Nguyen, Giang [2 ]
Tam, Wilson [1 ]
机构
[1] Natl Univ Singapore, Yong Loo Lin Sch Med, Alice Lee Ctr Nursing Studies, Singapore, Singapore
[2] RMIT Univ, Sch Sci Engn & Technol, 702 Nguyen Van Linh Blvd,Dist 7, Ho Chi Minh City 756000, Vietnam
关键词
Generative artificial intelligence; Large language model; Nursing; Technology;
D O I
10.1093/eurjcn/zvad120
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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.
引用
收藏
页码:549 / 552
页数:4
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