Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey
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 n...
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Elsevier BV
2024
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Online Access: | https://openaccess.city.ac.uk/id/eprint/32562/ https://openaccess.city.ac.uk/id/eprint/32562/8/1-s2.0-S1078817424000579-main.pdf https://doi.org/10.1016/j.radi.2024.02.020 |
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ftcityunivlondon:oai:openaccess.city.ac.uk:32562 2024-04-21T08:01:50+00:00 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. 2024-05-31 text https://openaccess.city.ac.uk/id/eprint/32562/ https://openaccess.city.ac.uk/id/eprint/32562/8/1-s2.0-S1078817424000579-main.pdf https://doi.org/10.1016/j.radi.2024.02.020 en eng Elsevier BV https://openaccess.city.ac.uk/id/eprint/32562/8/1-s2.0-S1078817424000579-main.pdf Pedersen, M. R. V., Kusk, M. W., Lysdahlgaard, S. , Mork-Knudsen, H., Malamateniou, C. https://openaccess.city.ac.uk/view/creators_id/christina=2Emalamateniou.html orcid:0000-0002-2352-8575 orcid:0000-0002-2352-8575 Jensen, J.view all authorsEPJS_limit_names_shown_load( 'creators_name_32562_et_al', 'creators_name_32562_rest' ); (2024). Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey. Radiography, 30(3), pp. 776-783. doi:10.1016/j.radi.2024.02.020 https://doi.org/10.1016/j.radi.2024.02.020 doi:10.1016/j.radi.2024.02.020 cc_by_4 QA75 Electronic computers. Computer science RC Internal medicine Article PeerReviewed 2024 ftcityunivlondon https://doi.org/10.1016/j.radi.2024.02.020 2024-03-27T17:47:31Z 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 ... Article in Journal/Newspaper Faroe Islands Greenland Iceland City University London: City Research Online Radiography 30 3 776 783 |
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City University London: City Research Online |
op_collection_id |
ftcityunivlondon |
language |
English |
topic |
QA75 Electronic computers. Computer science RC Internal medicine |
spellingShingle |
QA75 Electronic computers. Computer science RC Internal medicine Pedersen, M. R. V. Kusk, M. W. Lysdahlgaard, S. Mork-Knudsen, H. Malamateniou, C. Jensen, J. Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey |
topic_facet |
QA75 Electronic computers. Computer science RC Internal medicine |
description |
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 ... |
format |
Article in Journal/Newspaper |
author |
Pedersen, M. R. V. Kusk, M. W. Lysdahlgaard, S. Mork-Knudsen, H. Malamateniou, C. Jensen, J. |
author_facet |
Pedersen, M. R. V. Kusk, M. W. Lysdahlgaard, S. Mork-Knudsen, H. Malamateniou, C. Jensen, J. |
author_sort |
Pedersen, M. R. V. |
title |
Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey |
title_short |
Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey |
title_full |
Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey |
title_fullStr |
Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey |
title_full_unstemmed |
Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey |
title_sort |
nordic radiographers’ and students’ perspectives on artificial intelligence – a cross-sectional online survey |
publisher |
Elsevier BV |
publishDate |
2024 |
url |
https://openaccess.city.ac.uk/id/eprint/32562/ https://openaccess.city.ac.uk/id/eprint/32562/8/1-s2.0-S1078817424000579-main.pdf https://doi.org/10.1016/j.radi.2024.02.020 |
genre |
Faroe Islands Greenland Iceland |
genre_facet |
Faroe Islands Greenland Iceland |
op_relation |
https://openaccess.city.ac.uk/id/eprint/32562/8/1-s2.0-S1078817424000579-main.pdf Pedersen, M. R. V., Kusk, M. W., Lysdahlgaard, S. , Mork-Knudsen, H., Malamateniou, C. https://openaccess.city.ac.uk/view/creators_id/christina=2Emalamateniou.html orcid:0000-0002-2352-8575 orcid:0000-0002-2352-8575 Jensen, J.view all authorsEPJS_limit_names_shown_load( 'creators_name_32562_et_al', 'creators_name_32562_rest' ); (2024). Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey. Radiography, 30(3), pp. 776-783. doi:10.1016/j.radi.2024.02.020 https://doi.org/10.1016/j.radi.2024.02.020 doi:10.1016/j.radi.2024.02.020 |
op_rights |
cc_by_4 |
op_doi |
https://doi.org/10.1016/j.radi.2024.02.020 |
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Radiography |
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30 |
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3 |
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