Walsh Gemma, Stogiannos Nikolaos, van de Venter Riaan, Rainey Clare, Tam Winnie, McFadden Sonyia, McNulty Jonathan P, Mekis Nejc, Lewis Sarah, O'Regan Tracy, Kumar Amrita, Huisman Merel, Bisdas Sotirios, Kotter Elmar, Pinto Dos Santos Daniel, Sá Dos Reis Cláudia, van Ooijen Peter, Brady Adrian P, Malamateniou Christina
Division of Midwifery & Radiography, City University of London, London, United Kingdom.
School of Health Sciences, Ulster University, Derry~Londonderry, Northern Ireland.
BJR Open. 2023 Jun 30;5(1):20230033. doi: 10.1259/bjro.20230033. eCollection 2023.
Artificial intelligence (AI) has transitioned from the lab to the bedside, and it is increasingly being used in healthcare. Radiology and Radiography are on the frontline of AI implementation, because of the use of big data for medical imaging and diagnosis for different patient groups. Safe and effective AI implementation requires that responsible and ethical practices are upheld by all key stakeholders, that there is harmonious collaboration between different professional groups, and customised educational provisions for all involved. This paper outlines key principles of ethical and responsible AI, highlights recent educational initiatives for clinical practitioners and discusses the synergies between all medical imaging professionals as they prepare for the digital future in Europe. Responsible and ethical AI is vital to enhance a culture of safety and trust for healthcare professionals and patients alike. Educational and training provisions for medical imaging professionals on AI is central to the understanding of basic AI principles and applications and there are many offerings currently in Europe. Education can facilitate the transparency of AI tools, but more formalised, university-led training is needed to ensure the academic scrutiny, appropriate pedagogy, multidisciplinarity and customisation to the learners' unique needs are being adhered to. As radiographers and radiologists work together and with other professionals to understand and harness the benefits of AI in medical imaging, it becomes clear that they are faced with the same challenges and that they have the same needs. The digital future belongs to multidisciplinary teams that work seamlessly together, learn together, manage risk collectively and collaborate for the benefit of the patients they serve.
人工智能（AI）已从实验室走向临床，且在医疗保健领域的应用日益广泛。放射学和放射成像处于人工智能应用的前沿，这是因为针对不同患者群体的医学成像和诊断使用了大数据。安全有效地实施人工智能要求所有关键利益相关者秉持负责任和符合道德的做法，不同专业群体之间要进行和谐协作，并为所有相关人员提供定制化教育。本文概述了符合道德和负责任的人工智能的关键原则，强调了针对临床从业者的近期教育举措，并讨论了所有医学成像专业人员在为欧洲的数字未来做准备时的协同作用。负责任和符合道德的人工智能对于增强医疗保健专业人员和患者的安全与信任文化至关重要。为医学成像专业人员提供关于人工智能的教育和培训对于理解人工智能的基本原理和应用至关重要，目前欧洲有很多此类课程。教育可以促进人工智能工具的透明度，但需要更正规、由大学主导的培训来确保学术审查、适当的教学方法、多学科性以及满足学习者的独特需求。随着放射技师和放射科医生与其他专业人员共同努力，以理解和利用人工智能在医学成像中的益处，很明显他们面临着相同的挑战，有着相同的需求。数字未来属于能够无缝协作、共同学习、集体管理风险并为所服务的患者利益而合作的多学科团队。
