Department of Radiology and Nuclear Medicine, Erasmus MC - Sophia's Children's Hospital, Rotterdam, The Netherlands.
Department of Medical Sciences, University of Cagliari, Cagliari, Italy.
Pediatr Radiol. 2024 Apr;54(4):585-593. doi: 10.1007/s00247-023-05746-y. Epub 2023 Sep 4.
Over the past decade, there has been a dramatic rise in the interest relating to the application of artificial intelligence (AI) in radiology. Originally only 'narrow' AI tasks were possible; however, with increasing availability of data, teamed with ease of access to powerful computer processing capabilities, we are becoming more able to generate complex and nuanced prediction models and elaborate solutions for healthcare. Nevertheless, these AI models are not without their failings, and sometimes the intended use for these solutions may not lead to predictable impacts for patients, society or those working within the healthcare profession. In this article, we provide an overview of the latest opinions regarding AI ethics, bias, limitations, challenges and considerations that we should all contemplate in this exciting and expanding field, with a special attention to how this applies to the unique aspects of a paediatric population. By embracing AI technology and fostering a multidisciplinary approach, it is hoped that we can harness the power AI brings whilst minimising harm and ensuring a beneficial impact on radiology practice.
在过去的十年中,人们对人工智能(AI)在放射学中的应用产生了浓厚的兴趣。最初只能实现“狭义”的 AI 任务;然而,随着数据的日益丰富,以及强大的计算机处理能力的易于获取,我们越来越能够为医疗保健生成复杂而微妙的预测模型和精心设计的解决方案。然而,这些 AI 模型并非没有缺陷,有时这些解决方案的预期用途可能不会给患者、社会或医疗保健行业的从业者带来可预测的影响。在本文中,我们概述了关于 AI 伦理、偏见、局限性、挑战和应考虑因素的最新观点,这些都应该在这个令人兴奋且不断发展的领域中加以考虑,特别关注其如何适用于儿科人群的独特方面。通过采用 AI 技术并培养多学科方法,我们希望能够利用 AI 带来的力量,同时将伤害降到最低,并确保对放射科实践产生有益的影响。