
A survey of over 900 women reveals substantial variation in acceptance and expectations of AI in mammography depending on healthcare setting and demographics.
Key Details
- 1UT Southwestern surveyed 924 women across safety-net and academic medical centers between 2023–2024.
- 2Participants at academic centers were generally older, more educated, wealthier, and had higher self-reported AI knowledge.
- 3Higher education and AI knowledge correlated with greater acceptance of AI; non-Hispanic Black participants showed lower acceptance.
- 4Only 7% of women were comfortable with AI acting as the sole interpreter; 84% wanted a radiologist to review AI-detected abnormalities.
- 5Approximately 72% supported AI deployment in mammogram interpretation, but most preferred to wait for human oversight.
- 6Safety-net patients were less accepting of AI compared to academic center patients.
Why It Matters
These findings highlight the importance of tailoring AI implementation strategies and communication efforts to different patient populations in radiology. Patient education, consent, and human oversight remain critical for building trust and ensuring equitable use of AI in breast imaging.

Source
Radiology Business
Related News

•Radiology Business
AI Analyzes Mammograms to Assess Post-Surgery Breast Cancer Recurrence Risk
A new AI tool predicts likelihood of breast cancer recurrence after surgery using pre-operative mammograms.

•Radiology Business
AI Model Aims to Detect Placenta Accreta Earlier in Pregnancy
Researchers present a new AI model to help diagnose placenta accreta spectrum before delivery.

•AuntMinnie
Deep Learning Super-Resolution Boosts Accuracy of Coronary CT Angiography
Super-resolution deep learning reconstruction (SR-DLR) outperforms hybrid iterative reconstruction in coronary CT angiography for stenosis assessment.