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Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment

Author

Listed:
  • Maame Esi Woode

    (Monash University
    Monash University)

  • Udeni De Silva Perera

    (Monash University
    Deakin University)

  • Chris Degeling

    (University of Wollongong)

  • Yves Saint James Aquino

    (University of Wollongong)

  • Nehmat Houssami

    (University of Sydney
    The University of Sydney, a Joint Venture with Cancer Council)

  • Stacy M. Carter

    (University of Wollongong)

  • Gang Chen

    (Monash University
    University of Melbourne
    Peter MacCallum Cancer Centre)

Abstract

Background Breast cancer screening is considered an effective early detection strategy. Artificial intelligence (AI) may both offer benefits and create risks for breast screening programmes. To use AI in health screening services, the views and expectations of consumers are critical. This study examined the preferences of Australian women regarding AI use in breast cancer screening and the impact of information on preferences using discrete choice experiments. Methods The experiment presented two alternative screening services based on seven attributes (reading method, screening sensitivity, screening specificity, time between screening and receiving results, supporting evidence, fair representation, and who should be held accountable) to 2063 women aged between 40 and 74 years recruited from an online panel. Participants were randomised into two arms. Both received standard information on AI use in breast screening, but one arm received additional information on its potential benefits. Preferences for hypothetical breast cancer screening services were modelled using a random parameter logit model. Relative attribute importance and uptake rates were estimated. Results Participants preferred mixed reading (radiologist + AI system) over the other two reading methods. They showed a strong preference for fewer missed cases with a high attribute relative importance. Fewer false positives and a shorter waiting time for results were also preferred. Strength of preferences for mixed reading was significantly higher compared to two radiologists when additional information on AI is provided, highlighting the impact of information. Conclusions This study revealed the preferences among Australian women for the use of AI-driven breast cancer screening services. Results generally suggest women are open to their mammograms being read by both a radiologist and an AI-based system under certain conditions.

Suggested Citation

  • Maame Esi Woode & Udeni De Silva Perera & Chris Degeling & Yves Saint James Aquino & Nehmat Houssami & Stacy M. Carter & Gang Chen, 2025. "Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 18(5), pages 495-510, September.
  • Handle: RePEc:spr:patien:v:18:y:2025:i:5:d:10.1007_s40271-025-00742-w
    DOI: 10.1007/s40271-025-00742-w
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