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

Högberg, Charlotte LU orcid ; Larsson, Stefan LU and Lång, Kristina LU (2023) In BMJ Health & Care Informatics 30(1). p.1-8
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Artificial intelligence, Mammography, Screening, Radiologists, Clinical Decision-Making, Information Studies, social informatics
in
BMJ Health & Care Informatics
volume
30
issue
1
article number
e100712
pages
1 - 8
publisher
BMJ Publishing Group
external identifiers
  • scopus:85159799251
  • pmid:37217249
ISSN
2632-1009
DOI
10.1136/bmjhci-2022-100712
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
language
English
LU publication?
yes
id
0b8c697f-a264-42df-a984-3d6741136b47
alternative location
https://informatics.bmj.com/content/30/1/e100712
date added to LUP
2023-05-08 19:38:45
date last changed
2023-08-22 03:00:10
@article{0b8c697f-a264-42df-a984-3d6741136b47,
  abstract     = {{Objectives: <br/>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.<br/><br/>Methods:<br/>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.<br/><br/>Results:<br/>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.<br/><br/>Conclusions:<br/>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.}},
  author       = {{Högberg, Charlotte and Larsson, Stefan and Lång, Kristina}},
  issn         = {{2632-1009}},
  keywords     = {{Artificial intelligence; Mammography; Screening; Radiologists; Clinical Decision-Making; Information Studies; social informatics}},
  language     = {{eng}},
  month        = {{05}},
  number       = {{1}},
  pages        = {{1--8}},
  publisher    = {{BMJ Publishing Group}},
  series       = {{BMJ Health & Care Informatics}},
  title        = {{Anticipating Artificial Intelligence in Mammography Screening : Views of Swedish Breast Radiologists}},
  url          = {{https://lup.lub.lu.se/search/files/147194354/Hoegberg_Anticipating_artificial_intelligence_in_mammography_screening_Views_of_Swedish_breast_radiologists.pdf}},
  doi          = {{10.1136/bmjhci-2022-100712}},
  volume       = {{30}},
  year         = {{2023}},
}