ArticleBMJ health & care informatics2021
Women's attitudes to the use of AI image readers: a case study from a national breast screening programme.
Article in BMJ health & care informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
41 citing papers in PubMed, 4 syntheses or guidelines pooled it, 64 citations in OpenAlex.
- Ethical implications of the use of AI-based technologies for medical image classification systems in screening: a qualitative systematic review.Health technology assessment (Winchester, England) · 2026Pooled it
- Opportunities and challenges of artificial intelligence in public health: a systematic review on technological efficacy, ethical dilemmas, and governance pathways.Frontiers in public health · 2025Pooled it
- Frequency and characteristics of errors by artificial intelligence (AI) in reading screening mammography: a systematic review.Breast cancer research and treatment · 2024Pooled it
- Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence.Journal of medical Internet research · 2023Pooled it
- Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment.The patient · 2025Trial
- Patient perceptions and attitudes towards the use of artificial intelligence in the symptomatic breast unit.European radiology · 2026Article
- Constructs Influencing Patient Perceptions of Use of AI in Medical Imaging Analysis: Systematic Review.Interactive journal of medical research · 2026Review
- Reply to the Letter to the Editor: Methodological considerations in assessing patient perspectives on artificial intelligence in symptomatic breast imaging.European radiology · 2026Article
- Letter to the Editor: Methodological considerations in assessing patient perspectives on artificial intelligence in symptomatic breast imaging.European radiology · 2026Article
- Patient and Public Perceptions of Artificial Intelligence in Breast Imaging and Clinical Decision-Making: An Exploratory Cross-Sectional Survey Study.Diagnostics (Basel, Switzerland) · 2026Article
- Patient Perspectives on the Use of Artificial Intelligence in Malignant Melanoma Diagnosis.Dermatology practical & conceptual · 2026Article
- Bridging Pixels and Practice: AI-Assisted Mammography as a Next-Generation Diagnostic Strategy for Breast Cancer Screening.Diagnostics (Basel, Switzerland) · 2026Review
- Acceptability of Using Artificial Intelligence in the National Health Service Breast Screening Program: A Randomized Online Survey of Screening-Eligible Women in England.Mayo Clinic proceedings. Digital health · 2026Article
- The impact of AI on modern oncology from early detection to personalized cancer treatment.NPJ precision oncology · 2026Review
- Key Information Influencing Patient Decision-Making About AI in Health Care: Survey Experiment Study.Journal of medical Internet research · 2026Article
- Patients' views on the use of artificial intelligence in healthcare: Artificial Intelligence Survey Aachen (AISA)-a prospective survey.Insights into imaging · 2026Article
- Artificial intelligence and breast cancer screening in Serbia: a dual-perspective qualitative study among radiologists and screening-aged women.Frontiers in radiology · 2026Article
- Developing a Typology of Women's Attitudes Towards AI Use in the BreastScreen Programme-A Qualitative Study With BreastScreen Victoria Clients.Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Knowledge, Attitude, and Practice on Atrial Fibrillation and Atrial Fibrillation Screening in High-Risk Population: A Cross-Sectional Study.Aging medicine (Milton (N.S.W)) · 2025Article
- Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation.Journal of participatory medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundResearchers and developers are evaluating the use of mammogram readers that use artificial intelligence (AI) in clinical settings.
objectivesThis study examines the attitudes of women, both current and future users of breast screening, towards the use of AI in mammogram reading.
methodsWe used a cross-sectional, mixed methods study design with data from the survey responses and focus groups. We researched in four National Health Service hospitals in England. There we approached female workers over the age of 18 years and their immediate friends and family. We collected 4096 responses.
resultsThrough descriptive statistical analysis, we learnt that women of screening age (≥50 years) were less likely than women under screening age to use technology apps for healthcare advice (likelihood ratio=0.85, 95% CI 0.82 to 0.89, p<0.001). They were also less likely than women under screening age to agree that AI can have a positive effect on society (likelihood ratio=0.89, 95% CI 0.84 to 0.95, p<0.001). However, they were more likely to feel positive about AI used to read mammograms (likelihood ratio=1.09, 95% CI 1.02 to 1.17, p=0.009). DISCUSSION AND
conclusionsWomen of screening age are ready to accept the use of AI in breast screening but are less likely to use other AI-based health applications. A large number of women are undecided, or had mixed views, about the use of AI generally and they remain to be convinced that it can be trusted.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.