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'Humans think outside the pixels' - Radiologists' perceptions of using artificial intelligence for breast cancer detection in mammography screening in a clinical setting
Uppsala Univ, Ctr Res Eth & Bioeth, Dept Publ Hlth & Caring Sci, Box 564, S-75105 Uppsala, Sweden..
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment. Inst Futures Studies, Stockholm, Sweden..ORCID iD: 0000-0002-5290-5704
2024 (English)In: Health Informatics Journal, ISSN 1460-4582, E-ISSN 1741-2811, Vol. 30, no 3, article id 14604582241275020Article in journal (Refereed) Published
Abstract [en]

Objective

This study aimed to explore radiologists’ views on using an artificial intelligence (AI) tool named ScreenTrustCAD with Philips equipment) as a diagnostic decision support tool in mammography screening during a clinical trial at Capio Sankt Göran Hospital, Sweden.

Methods

We conducted semi-structured interviews with seven breast imaging radiologists, evaluated using inductive thematic content analysis.

Results

We identified three main thematic categories: AI in society, reflecting views on AI’s contribution to the healthcare system; AI-human interactions, addressing the radiologists’ self-perceptions when using the AI and its potential challenges to their profession; and AI as a tool among others. The radiologists were generally positive towards AI, and they felt comfortable handling its sometimes-ambiguous outputs and erroneous evaluations. While they did not feel that it would undermine their profession, they preferred using it as a complementary reader rather than an independent one.

Conclusion

The results suggested that breast radiology could become a launch pad for AI in healthcare. We recommend that this exploratory work on subjective perceptions be complemented by quantitative assessments to generalize the findings.

Place, publisher, year, edition, pages
SAGE Publications , 2024. Vol. 30, no 3, article id 14604582241275020
Keywords [en]
acceptance, artificial intelligence, breast imaging, decision support, radiology
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:kth:diva-353789DOI: 10.1177/14604582241275020ISI: 001293010700001PubMedID: 39155239Scopus ID: 2-s2.0-85201571670OAI: oai:DiVA.org:kth-353789DiVA, id: diva2:1900516
Note

QC 20240924

Available from: 2024-09-24 Created: 2024-09-24 Last updated: 2024-09-24Bibliographically approved

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Engström, Emma

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