Anticipating Artificial Intelligence in Mammography Screening : Views of Swedish Breast Radiologists

Högberg, Charlotte; Larsson, Stefan; Lång, Kristina (2023-05-22). Anticipating Artificial Intelligence in Mammography Screening : Views of Swedish Breast Radiologists. BMJ Health & Care Informatics, 30, (1), 1 - 8
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| Published | English
Authors:
Högberg, Charlotte ; Larsson, Stefan ; Lång, Kristina
Department:
Department of Technology and Society
AI and Society
eSSENCE: The e-Science Collaboration
LUCC: Lund University Cancer Centre
Radiology Diagnostics, Malmö
Project:
AI in the Name of the Common Good - Relations of data, AI and humans in health and public sector
Mammography Screening with Artificial Intelligence
AIR Lund - Artificially Intelligent use of Registers
Research Group:
AI and Society
Radiology Diagnostics, Malmö
Abstract:
Objectives:
Artificial intelligence (AI) is increasingly tested and integrated into breast cancer screening. Still, there are unresolved issues regarding its possible ethical, social and legal impacts. Furthermore, the perspectives of different actors are lacking. This study investigates the views of breast radiologists on AI-supported mammography screening, with a focus on attitudes, perceived benefits and risks, accountability of AI use, and potential impact on the profession.

Methods:
We conducted an online survey of Swedish breast radiologists. As early adopter of breast cancer screening, and digital technologies, Sweden is a particularly interesting case to study. The survey had different themes, including: attitudes and responsibilities pertaining to AI, and AI’s impact on the profession. Responses were analysed using descriptive statistics and correlation analyses. Free texts and comments were analysed using an inductive approach.

Results:
Overall, respondents (47/105, response rate 44.8%) were highly experienced in breast imaging and had a mixed knowledge of AI. A majority (n=38, 80.8%) were positive/somewhat positive towards integrating AI in mammography screening. Still, many considered there to be potential risks to a high/somewhat high degree (n=16, 34.1%) or were uncertain (n=16, 34.0%). Several important uncertainties were identified, such as defining liable actor(s) when AI is integrated into medical decision-making.

Conclusions:
Swedish breast radiologists are largely positive towards integrating AI in mammography screening, but there are significant uncertainties that need to be addressed, especially regarding risks and responsibilities. The results stress the importance of understanding actor-specific and context-specific challenges to responsible implementation of AI in healthcare.
Keywords:
Artificial intelligence ; Mammography ; Screening ; Radiologists ; Clinical Decision-Making ; Information Studies ; social informatics ; Information Systems, Social aspects ; Sociology (excluding Social Work, Social Psychology and Social Anthropology) ; Radiology, Nuclear Medicine and Medical Imaging
ISSN:
2632-1009
LUP-ID:
0b8c697f-a264-42df-a984-3d6741136b47 | Link: https://lup.lub.lu.se/record/0b8c697f-a264-42df-a984-3d6741136b47 | Statistics

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