An Australasian survey on the use of ChatGPT and other large language models in medical physics.

IF 2 4区 医学 Q3 ENGINEERING, BIOMEDICAL
Stanley A Norris, Tomas Kron, Maeve Masterson, Mohamed K Badawy
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引用次数: 0

Abstract

This study surveyed medical physicists in Australia and New Zealand on their use of large language models (LLMs), particularly ChatGPT. There is currently no literature on the application of ChatGPT and other LLMs by medical physicists. This survey targeted a mixed group of professionals, including clinical medical physicists, registrars, students, and other specialised roles. It reveals that many respondents integrate LLM platforms into their work for a broad range of tasks. Most participants reported efficiency gains, although fewer perceived improvements in the overall quality of their work. Despite these benefits, substantial concerns remain regarding data security, patient confidentiality, and the lack of established guidelines or professional training for using these tools in a clinical context. Further, the potential for sudden changes in accessibility and pricing, which could disproportionately impact developing countries and under-resourced departments, implies that other vulnerabilities may exist. These findings suggest the need for the medical physics community to come together and debate the careful balance between exploiting LLM platforms and developing clear best practices that implement robust risk management strategies.

一项关于在医学物理学中使用ChatGPT和其他大型语言模型的澳大利亚调查。
这项研究调查了澳大利亚和新西兰的医学物理学家对大型语言模型(llm)的使用,特别是ChatGPT。目前还没有医学物理学家应用ChatGPT等法学硕士的文献。这项调查针对的是一组混合的专业人员,包括临床医学物理学家、注册商、学生和其他专业人员。调查显示,许多受访者将法学硕士平台整合到他们的工作中,以完成广泛的任务。大多数参与者都表示效率得到了提高,尽管很少有人认为他们的整体工作质量得到了改善。尽管有这些好处,但在数据安全、患者机密性以及缺乏在临床环境中使用这些工具的既定指南或专业培训方面,仍然存在实质性的担忧。此外,可及性和定价方面的突然变化可能对发展中国家和资源不足的部门产生不成比例的影响,这意味着可能存在其他脆弱性。这些发现表明,医学物理学界需要聚集在一起,讨论利用法学硕士平台和制定实施稳健风险管理策略的明确最佳实践之间的谨慎平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.40
自引率
4.50%
发文量
110
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