Potential applications and implications of large language models in primary care

初级保健 小学(天文学) 心理学 计算机科学 医学 家庭医学 物理 天体物理学
作者
Ann Andrew
出处
期刊:Family Medicine and Community Health [BMJ]
卷期号:12 (Suppl 1): e002602-e002602
标识
DOI:10.1136/fmch-2023-002602
摘要

The recent release of highly advanced generative artificial intelligence (AI) chatbots, including ChatGPT and Bard, which are powered by large language models (LLMs), has attracted growing mainstream interest over its diverse applications in clinical practice, including in health and healthcare. The potential applications of LLM-based programmes in the medical field range from assisting medical practitioners in improving their clinical decision-making and streamlining administrative paperwork to empowering patients to take charge of their own health. However, despite the broad range of benefits, the use of such AI tools also comes with several limitations and ethical concerns that warrant further consideration, encompassing issues related to privacy, data bias, and the accuracy and reliability of information generated by AI. The focus of prior research has primarily centred on the broad applications of LLMs in medicine. To the author’s knowledge, this is, the first article that consolidates current and pertinent literature on LLMs to examine its potential in primary care. The objectives of this paper are not only to summarise the potential benefits, risks and challenges of using LLMs in primary care, but also to offer insights into considerations that primary care clinicians should take into account when deciding to adopt and integrate such technologies into their clinical practice.
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