Preparing for Implementing Commercial Algorithms in Radiology: A Formative Evaluation Study

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dc.contributor.authorSilsand, Line
dc.contributor.authorSeverinsen, Gro-Hilde
dc.contributor.authorKannelønning, Mari Serine
dc.date.accessioned2023-08-29T07:56:32Z
dc.date.available2023-08-29T07:56:32Z
dc.date.issued2023
dc.description.abstractThis paper aims to contribute to a better understanding of the practical preparations necessary for adopting and scaling AI solutions in clinical radiology. Based on a longitudinal qualitative case study of a Norwegian health trust’s AI procurement for radiology and the trust’s further implementation preparations, the paper explores the following research questions: How does the healthcare organisation prepare for implementing CE-marked algorithms? How can a healthcare organisation establish acceptance among radiologists when implementing commercially available AI solutions for ...en
dc.identifier.doi10.48340/ihc2023_p010
dc.identifier.issn2510-2591
dc.identifier.urihttps://dl.eusset.eu/handle/20.500.12015/5032
dc.language.isoen
dc.publisherEuropean Society for Socially Embedded Technologies (EUSSET)
dc.relation.ispartofInfrahealth 2023 - Proceedings of the 9th International Conference on Infrastructures in Healthcare 2023
dc.relation.ispartofseriesReports of the European Society for Socially Embedded Technologies: vol. 7, no. 4
dc.titlePreparing for Implementing Commercial Algorithms in Radiology: A Formative Evaluation Studyen
dc.typeText/Conference Paper
gi.conference.date11-12 September 2023
gi.conference.locationSiegen, Germany

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