Artificial intelligence: Augmenting telehealth with large language models

被引:18
|
作者
Snoswell, Centaine L. [1 ,2 ,5 ,6 ]
Snoswell, Aaron J. [4 ]
Kelly, Jaimon T. [1 ,2 ]
Caffery, Liam J. [1 ,2 ]
Smith, Anthony C. [1 ,2 ,3 ]
机构
[1] Univ Queensland, Ctr Online Hlth, Brisbane, Australia
[2] Univ Queensland, Ctr Hlth Serv Res, Brisbane, Australia
[3] Univ Southern Denmark, Ctr Innovat Med Technol, Odense, Denmark
[4] Queensland Univ Technol, Australian Res Council Ctr Excellence Automated De, Brisbane, Australia
[5] Univ Queensland, Ctr Online Hlth, Ctr Hlth Serv Res, Brisbane, Australia
[6] Princess Alexandra Hosp, Ctr Online Hlth, Ground Floor Bldg 33, Woolloongabba, Qld 4102, Australia
基金
芬兰科学院; 澳大利亚研究理事会;
关键词
Machine learning; large language models; ChatGPT; telehealth; telemedicine; digital health; artificial intelligence;
D O I
10.1177/1357633X231169055
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
This brief editorial describes an emerging area of machine learning technology called large language models (LLMs). LLMs, such as ChatGPT, are the technological disruptor of this decade. They are going to be integrated into search engines (Bing and Google) and into Microsoft products in the coming months. They will therefore fundamentally change the way patients and clinicians access and receive information. It is essential that telehealth clinicians are aware of LLMs and appreciate their capabilities and limitations.
引用
收藏
页码:150 / 154
页数:5
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