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dc.contributor.authorMartiniussen, Marit Almenning
dc.contributor.authorLarsen, Marthe
dc.contributor.authorLarsen, Anne Sofie Frøyshov
dc.contributor.authorHovda, Tone
dc.contributor.authorKoch, Henrik Wethe
dc.contributor.authorBjørnerud, Atle
dc.contributor.authorHofvind, Solveig Sand-Hanssen
dc.date.accessioned2023-10-20T11:32:20Z
dc.date.available2023-10-20T11:32:20Z
dc.date.issued2023-08-23
dc.description.abstractPurpose: To explore Norwegian breast radiologists’ expectations of adding artificial intelligence (AI) in the interpretation procedure of screening mammograms.<p> <p>Methods: All breast radiologists involved in interpretation of screening mammograms in BreastScreen Norway during 2021 and 2022 (n = 98) were invited to take part in this anonymous cross-sectional survey about use of AI in mammographic screening. The questionnaire included background information of the respondents, their expectations, considerations of biases, and ethical and social implications of implementing AI in screen reading. Data was collected digitally and analyzed using descriptive statistics. <p>Results: The response rate was 61% (60/98), and 67% (40/60) of the respondents were women. Sixty percent (36/60) reported ≥10 years’ experience in screen reading, while 82% (49/60) reported no or limited experience with AI in health care. Eighty-two percent of the respondents were positive to explore AI in the interpretation procedure in mammographic screening. When used as decision support, 68% (41/60) expected AI to increase the radiologists’ sensitivity for cancer detection. As potential challenges, 55% (33/60) reported lack of trust in the AI system and 45% (27/60) reported discrepancy between radiologists and AI systems as possible challenges. The risk of automation bias was considered high among 47% (28/60). Reduced time spent reading mammograms was rated as a potential benefit by 70% (42/60). <p>Conclusion: The radiologists reported positive expectations of AI in the interpretation procedure of screening mammograms. Efforts to minimize the risk of automation bias and increase trust in the AI systems are important before and during future implementation of the tool.en_US
dc.identifier.citationMartiniussen, Larsen, Larsen, Hovda, Koch, Bjørnerud, Hofvind. Norwegian radiologists’ expectations of artificial intelligence in mammographic screening – A cross-sectional survey. European Journal of Radiology. 2023;167en_US
dc.identifier.cristinIDFRIDAID 2175818
dc.identifier.doi10.1016/j.ejrad.2023.111061
dc.identifier.issn0720-048X
dc.identifier.issn1872-7727
dc.identifier.urihttps://hdl.handle.net/10037/31593
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalEuropean Journal of Radiology
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleNorwegian radiologists’ expectations of artificial intelligence in mammographic screening – A cross-sectional surveyen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution 4.0 International (CC BY 4.0)