⚡ Quick Summary
A recent study explored the preferences of Australian women regarding the use of Artificial Intelligence (AI) in breast cancer screening. The findings indicate a strong preference for a mixed reading approach (radiologist + AI), particularly when informed about the potential benefits of AI.
🔍 Key Details
- 👩🔬 Participants: 2063 women aged 40-74
- 🧪 Methodology: Discrete choice experiments
- 📊 Attributes assessed: Reading method, sensitivity, specificity, waiting time, supporting evidence, fair representation, accountability
- 📈 Analysis: Random parameter logit model
🔑 Key Takeaways
- 🤖 Preference for mixed reading: Women favored a combination of radiologist and AI for screening.
- 📉 Importance of fewer missed cases: This attribute was highly valued by participants.
- ❌ Fewer false positives: A significant preference for reducing false positives was noted.
- ⏳ Shorter waiting times: Participants preferred quicker results from screenings.
- 📚 Impact of information: Providing additional information on AI’s benefits significantly influenced preferences.
- 🌍 Study location: Conducted in Australia, reflecting local consumer attitudes.
📚 Background
Breast cancer screening is a vital strategy for early detection, and the integration of AI into screening programs presents both opportunities and challenges. Understanding consumer preferences is essential for the successful implementation of AI technologies in healthcare settings. This study aimed to gauge the attitudes of Australian women towards AI in breast cancer screening, emphasizing the importance of informed decision-making.
🗒️ Study
The study involved a discrete choice experiment with 2063 women aged between 40 and 74 years, recruited from an online panel. Participants were presented with two hypothetical screening services characterized by seven attributes. The aim was to assess how these attributes influenced their preferences, particularly in the context of AI’s role in breast cancer screening.
📈 Results
The results revealed a clear preference for the mixed reading approach, where both a radiologist and an AI system analyze mammograms. Participants expressed a strong desire for fewer missed cases, indicating that this attribute held significant importance. Additionally, preferences for reduced false positives and shorter waiting times for results were also highlighted. Notably, the strength of preference for mixed reading increased when participants received additional information about AI’s potential benefits.
🌍 Impact and Implications
The findings of this study have important implications for the future of breast cancer screening in Australia. By understanding consumer preferences, healthcare providers can better tailor their services to meet the needs and expectations of women. The openness to AI-driven screening solutions suggests a promising avenue for enhancing early detection strategies, ultimately leading to improved patient outcomes.
🔮 Conclusion
This study underscores the potential of integrating AI into breast cancer screening programs, particularly when consumer preferences are taken into account. The positive reception of mixed reading approaches indicates a readiness among women to embrace technological advancements in healthcare, provided they are well-informed. Continued research and dialogue are essential to navigate the evolving landscape of AI in medical screening.
💬 Your comments
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Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment.
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.
Author: [‘Woode ME’, ‘De Silva Perera U’, ‘Degeling C’, ‘Aquino YSJ’, ‘Houssami N’, ‘Carter SM’, ‘Chen G’]
Journal: Patient
Citation: Woode ME, et al. Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment. Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment. 2025; (unknown volume):(unknown pages). doi: 10.1007/s40271-025-00742-w