Artificial intelligence: Augmenting telehealth with large language models

Author:

Snoswell Centaine L12ORCID,Snoswell Aaron J3,Kelly Jaimon T12ORCID,Caffery Liam J12ORCID,Smith Anthony C124ORCID

Affiliation:

1. Centre for Online Health, The University of Queensland, Brisbane, Australia

2. Centre for Health Services Research, The University of Queensland, Brisbane, Australia

3. Australian Research Council Centre of Excellence for Automated Decision Making and Society, Queensland University of Technology, Brisbane, Australia

4. Centre for Innovative Medical Technology, University of Southern Denmark, Odense, Denmark

Abstract

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.

Publisher

SAGE Publications

Subject

Health Informatics

Reference13 articles.

1. Smith S, Patwary M, Norick B, et al. Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model. arXiv preprint arXiv:220111990. 2022.

2. Row over Babylon’s chatbot shows lack of regulation

3. Pharmacist vs machine: Pharmacy services in the age of large language models

4. On the Dangers of Stochastic Parrots

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