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Nordic radiographers' and students' perspectives on artificial intelligence - A cross-sectional online survey.
Pedersen, M R V; Kusk, M W; Lysdahlgaard, S; Mork-Knudsen, H; Malamateniou, C; Jensen, J.
Afiliação
  • Pedersen MRV; Department of Radiology, Vejle Hospital - Part of Lillebaelt Hospital, Vejle, Denmark; Department of Radiology, Kolding Hospital- Part of Lillebaelt Hospital, Kolding, Denmark; Department of Regional Health Research, University of Southern Denmark, Odense, Denmark; Discipline of Medical Imaging &amp
  • Kusk MW; Department of Regional Health Research, University of Southern Denmark, Odense, Denmark; Department of Radiology and Nuclear Medicine, University Hospital of Southern Denmark, Esbjerg, Denmark; IRIS - Imaging Research Initiative Southwest, University Hospital of Southern Denmark, Esbjerg, Denmark; R
  • Lysdahlgaard S; Department of Regional Health Research, University of Southern Denmark, Odense, Denmark; Department of Radiology and Nuclear Medicine, University Hospital of Southern Denmark, Esbjerg, Denmark; IRIS - Imaging Research Initiative Southwest, University Hospital of Southern Denmark, Esbjerg, Denmark.
  • Mork-Knudsen H; Department of Radiology, Haukeland University Hospital, Norway.
  • Malamateniou C; Department of Radiography, Division of Midwifery and Radiography, School of Health and Psychological Sciences, City, University of London, UK; European Federation of Radiographer Societies, Churchilllaan 11, 3527 GV, Utrecht, the Netherlands.
  • Jensen J; Research and Innovation Unit of Radiology, University of Southern Denmark, Odense, Denmark; Department of Radiology, Odense University Hospital, Odense, Denmark.
Radiography (Lond) ; 30(3): 776-783, 2024 05.
Article em En | MEDLINE | ID: mdl-38461583
ABSTRACT

INTRODUCTION:

The integration of artificial intelligence (AI) into the domain of radiography holds substantial potential in various aspects including workflow efficiency, image processing, patient positioning, and quality assurance. The successful implementation of AI within a Radiology department necessitates the participation of key stakeholders, particularly radiographers. The study aimed to provide a comprehensive investigation about Nordic radiographers' perspectives and attitudes towards AI in radiography.

METHODS:

An online 29-item survey was distributed via social media platforms to Nordic students and radiographers working in Denmark, Norway, Sweden, Iceland, Greenland, and the Faroe Islands including items on demographics, specialization, educational background, place of work and perspectives and knowledge on AI. The items were a mix of closed-type and scaled questions, with the option for free-text responses when relevant.

RESULTS:

The survey received responses from all Nordic countries with 586 respondents, 26.8% males, 72.1% females, and 1.1% non-binary/self-defined or preferred not to say. The mean age was 37.2 with a standard deviation (SD) of ±12.1 years, and the mean number of years since qualification was 14.2 SD ± 10.3 years. A total of 43% (n = 254) of the respondents had not received any AI training in clinical practice. Whereas 13% (n = 76) had received AI during radiography undergrad training. A total of 77.9% (n = 412) expressed interest in pursuing AI education. The majority of respondents were aware of the potential use of AI (n = 485, 82.8%) and 39.1% (n = 204) had no reservations about AI.

CONCLUSION:

Overall, this study found that Nordic radiographers have a positive attitude toward AI. Very limited training or education has been provided to the radiographers. Especially since 82.8% reports on plans to implement AI in clinical practice. In general, awareness of AI applications is high, but the educational level is low for Nordic radiographers. IMPLICATION FOR PRACTICE This study emphasises the favourable view of AI held by students and Nordic radiographers. However, there is a need for continuous professional development to facilitate the implementation and effective utilization of AI tools within the field of radiography.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Atitude do Pessoal de Saúde Limite: Adult / Female / Humans / Male País como assunto: Europa Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Atitude do Pessoal de Saúde Limite: Adult / Female / Humans / Male País como assunto: Europa Idioma: En Ano de publicação: 2024 Tipo de documento: Article