当一种方式不适合所有人-人工智能在澳大利亚农村健康

IF 1.9 4区 医学 Q2 NURSING
Lewis Hains, Joshua G. Kovoor, Brandon Stretton, Aashray K. Gupta, Ammar Zaka, Gavin Carmichael, John M. Kefalianos, Win Le Shwe Sin Ei, Alasdair Leslie, Andrew Booth, Shrirajh Satheakeerthy, Alexander Beath, Yasser Arafat, Mathew O. Jacob, Martin Bruening, Weng Onn Chan, Stephen Bacchi
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引用次数: 0

摘要

人工智能(AI)正在对我们日常生活的许多方面产生越来越大的影响。这种变化在医疗保健领域也是如此,开发了各种工具来加速繁重的行政任务并提高整体医疗保健效率,特别是在大都市中心。人工智能在澳大利亚农村、区域和偏远地区的医院仍然相对清晰,在这些地方人工智能有可能提供重大好处。与以往的卫生技术实施一样,农村劳动力对人工智能维护和支持的需求可能会阻碍人工智能在这些地区的部署。虽然人工智能已在大都市地区成功实施,但这些模式在行政和医疗系统存在显著差异的农村卫生环境中的可转译性可能有限。人工智能方法可以帮助解决农村中心的关键问题,如资源分配和及时将患者转移到更高级别的护理。虽然人工智能在农村中心的潜在好处是显而易见的,但必须考虑到农村中心可能限制人工智能在这些医院取得成功的关键因素。农村人口较少可能会限制培训特定地点模型的能力,而连接问题可能会阻碍它们的有效使用。结论:需要做出具体努力,以实现澳大利亚农村医疗人工智能的潜在效益;解决农村地区的连通性和劳动力问题对于让人工智能和大型语言模型帮助农村中心受益至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
When One Size Does not Fit All—Artificial Intelligence in Australian Rural Health

Aims

Artificial intelligence (AI) is having an increasing impact on many aspects of our day-to-day lives. This change is also true in healthcare, with various tools being developed to hasten burdensome administrative tasks and increase overall healthcare efficiency, particularly in metropolitan centres.

Context

AI has remained comparatively clear of rural, regional and remote Australian hospitals, where it has the potential to provide significant benefits. Like previous health technology implementations, rural workforce requirements for AI maintenance and support may hinder AI deployment in these areas. While AI has been implemented successfully in metropolitan areas, these models may have limited translatability to rural health settings with significantly different administrative and healthcare systems.

Approach

AI may assist with key issues in rural centres such as resource allocation and timely patient transfer for higher level care. While the potential benefits of AI in rural centres are clear, one must consider key factors in rural centres that may limit the success of AI in these hospitals. Smaller rural populations may limit the ability to train location-specific models, and connectivity issues may impede their effective use.

Conclusion

Specific efforts are required to realise potential benefits of medical AI for rural Australia; addressing connectivity and workforce issues in rural areas is vital to allow for AI and large language models to help benefit rural centres.

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来源期刊
Australian Journal of Rural Health
Australian Journal of Rural Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
2.30
自引率
16.70%
发文量
122
审稿时长
12 months
期刊介绍: The Australian Journal of Rural Health publishes articles in the field of rural health. It facilitates the formation of interdisciplinary networks, so that rural health professionals can form a cohesive group and work together for the advancement of rural practice, in all health disciplines. The Journal aims to establish a national and international reputation for the quality of its scholarly discourse and its value to rural health professionals. All articles, unless otherwise identified, are peer reviewed by at least two researchers expert in the field of the submitted paper.
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