ReviewFuture healthcare journal2023
The implementation of artificial intelligence in radiology: a narrative review of patient perspectives.
Review in Future healthcare journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- Stakeholders' perspectives on an autonomous brain MRI: An interview study.PEC innovation · 2026Article
- Patient Perspectives on the Use of Artificial Intelligence in Malignant Melanoma Diagnosis.Dermatology practical & conceptual · 2026Article
- 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
- Implementing an Artificial Intelligence Decision Support System in Radiology: Prospective Qualitative Evaluation Study Using the Nonadoption Abandonment Scale-Up, Spread, and Sustainability (NASSS) Framework.Journal of medical Internet research · 2026Article
- Establishing a framework for development, prioritization, and assessment of artificial intelligence technology within the radiology department at a large UK teaching hospital.BJR artificial intelligence · 2026Review
- Large Language Models in Radiologist-Patient Communication: A Narrative Review for Clinical Practice.Cureus · 2026Review
- Public trust of AI in healthcare in South Africa: results of a survey.BMC medical ethics · 2025Article
- Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study.Journal of medical Internet research · 2025Article
- Acceptability of artificial intelligence in breast screening: focus groups with the screening-eligible population in England.BMJ public health · 2024Article
- Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review.JMIR human factors · 2024Article
- Looking back, looking forward.Future healthcare journal · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: To synthesise research on the view of the public and patients of the use of artificial intelligence (AI) in radiology investigations. Methods: A literature review of narrative synthesis of qualitative and quantitative studies that reported views of the public and patients toward the use of AI in radiology. Results: Only seven studies related to patient and public views were retrieved, suggesting that this is an underexplored area of research. Two broad themes, of confidence in the capabilities of AI, and the accountability and transparency of AI, were identified. Conclusions: Both optimism and concerns were expressed by participants. Transparency in the implementation of AI, scientific validation, clear regulation and accountability were expected. Combined human and AI interpretation of imaging was strongly favoured over AI acting autonomously. The review highlights the limited engagement of the public in the adoption of AI in a radiology setting. Successful implementation of AI in this field will require demonstrating not only adequate accuracy of the technology, but also its acceptance by patients.
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.