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Artificial intelligence and the medical physics profession - A Swedish perspective
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.ORCID iD: 0000-0002-0209-0463
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.ORCID iD: 0000-0002-8971-9788
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2021 (English)In: Physica medica (Testo stampato), ISSN 1120-1797, E-ISSN 1724-191X, Vol. 88, p. 218-225Article in journal (Refereed) Published
Abstract [en]

Background: There is a continuous and dynamic discussion on artificial intelligence (AI) in present-day society. AI is expected to impact on healthcare processes and could contribute to a more sustainable use of resources allocated to healthcare in the future. The aim for this work was to establish a foundation for a Swedish perspective on the potential effect of AI on the medical physics profession.

Materials and methods: We designed a survey to gauge viewpoints regarding AI in the Swedish medical physics community. Based on the survey results and present-day situation in Sweden, a SWOT analysis was performed on the implications of AI for the medical physics profession.

Results: Out of 411 survey recipients, 163 responded (40%). The Swedish medical physicists with a professional license believed (90%) that AI would change the practice of medical physics but did not foresee (81%) that AI would pose a risk to their practice and career. The respondents were largely positive to the inclusion of AI in educational programmes. According to self-assessment, the respondents’ knowledge of and workplace preparedness for AI was generally low.

Conclusions: From the survey and SWOT analysis we conclude that AI will change the medical physics profession and that there are opportunities for the profession associated with the adoption of AI in healthcare. To overcome the weakness of limited AI knowledge, potentially threatening the role of medical physicists, and build upon the strong position in Swedish healthcare, medical physics education and training should include learning objectives on AI.

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 88, p. 218-225
Keywords [en]
General Physics and Astronomy, Radiology Nuclear Medicine and imaging, General Medicine, Biophysics
National Category
Radiology, Nuclear Medicine and Medical Imaging Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-188606DOI: 10.1016/j.ejmp.2021.07.009ISI: 000687937600007PubMedID: 34304045Scopus ID: 2-s2.0-85111006975OAI: oai:DiVA.org:umu-188606DiVA, id: diva2:1603112
Available from: 2021-10-14 Created: 2021-10-14 Last updated: 2023-03-24Bibliographically approved

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Andersson, JonasNyholm, Tufve

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Andersson, JonasNyholm, TufveAlmén, AnjaOlsson, Lars E.
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