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Responsible AI practice and AI education are central to AI implementation: a rapid review for all medical imaging professionals in Europe.
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.
Afiliação
  • Walsh G; Division of Midwifery & Radiography, City University of London, London, United Kingdom.
  • Rainey C; School of Health Sciences, Ulster University, Derry~Londonderry, Northern Ireland.
  • Tam W; Division of Midwifery & Radiography, City University of London, London, United Kingdom.
  • McFadden S; School of Health Sciences, Ulster University, Coleraine, United Kingdom.
  • McNulty JP; University College Dublin, School of Medicine, Dublin, Ireland.
  • Mekis N; Medical Imaging and Radiotherapy Department, University of Ljubljana, Faculty of Health Sciences, Ljubljana, Slovenia.
  • Lewis S; Discipline of Medical Imaging Science, Sydney School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
  • O'Regan T; The Society and College of Radiographers, London, United Kingdom.
  • Kumar A; Frimley Health NHS Foundation Trust, Frimley, United Kingdom.
  • Huisman M; Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands.
  • Sá Dos Reis C; School of Health Sciences (HESAV), University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne, Switzerland.
BJR Open ; 5(1): 20230033, 2023.
Article em En | MEDLINE | ID: mdl-37953871
ABSTRACT
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.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Systematic_reviews Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Systematic_reviews Idioma: En Ano de publicação: 2023 Tipo de documento: Article