de Vries, Clarisse FlorenceColosimo, Samantha JBoyle, MoraghLip, GeraldAnderson, Lesley AStaff, Roger TiCAIRD Radiology Collaboration2022-12-122022-12-122022-12-09de Vries, C F, Colosimo, S J, Boyle, M, Lip, G, Anderson, L A, Staff, R T & iCAIRD Radiology Collaboration 2022, 'AI in breast screening mammography : breast screening readers' perspectives', Insights into Imaging, vol. 13, no. 1, 186. https://doi.org/10.1186/s13244-022-01322-41869-4101ORCID: /0000-0002-1000-3649/work/124674768https://hdl.handle.net/2164/19718Acknowledgements We would like to thank all the survey respondents for their time and input. We would also like to thank the Scottish Breast Radiology Forum (SBRF) and British Society of Breast Radiology (BSBR) for their aid in dissemination of the survey. Furthermore, we would like to thank Dr Rumana Newlands for her advice on how to perform content analysis and report its results. iCAIRD Radiology Collaboration team members: Harrison D (iCAIRD Director), University of St Andrews. Black C, Murray A and Wilde K, University of Aberdeen. Blackwood JD, NHS Greater Glasgow and Clyde. Butterly C and Zurowski J, University of Glasgow. Eilbeck J and McSkimming C, NHS Grampian. Canon Medical Research Europe Ltd. – SHAIP platform. Funding This work is supported by the Industrial Centre for Artificial Intelligence Research in Digital Diagnostics (iCAIRD) which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690]. The funding source was not involved in study design; collection, analysis and interpretation of data; writing of the report; or in the decision to submit the article for publication. Author info71216442engMammographyScreeningRadiologistBreast screening readerR MedicineUK Research and Innovation (UKRI)104690Supplementary InformationRJournal article10.1186/s13244-022-01322-4131