ReviewThe British journal of radiology2020
Artificial intelligence in diagnostic imaging: impact on the radiography profession.
Review in The British journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07558746 (AI Reliance in Diagnostic Radiology Among Intern Doctors in Palestine), which is not on this map. Cited by 70 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.
AI Reliance in Diagnostic Radiology Among Intern Doctors in Palestine: A Triple-Arm, Triple-Blind, Parallel-Design Randomized Controlled Trial
Who cites it
70 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Artificial intelligence for medical imaging education: bibliometric and visual analysis.Frontiers in medicine · 2026Pooled it
- Artificial intelligence in personalized computed tomography dose optimization: a systematic review of techniques and clinical outcomes.Frontiers in medicine · 2026Pooled it
- Physicians' required competencies in AI-assisted clinical settings: a systematic review.British medical bulletin · 2025Pooled it
- Artificial intelligence in risk prediction and diagnosis of vertebral fractures.Scientific reports · 2024Pooled it
- Triage and workflow optimization with artificial intelligence in pediatric imaging.Pediatric radiology · 2026Review
- Barriers, Facilitators, and Intention to Use AI for Breast Cancer Diagnosis: Mixed Methods Study Among Austrian Physicians With and Without AI Experience.Journal of medical Internet research · 2026Article
- Investigating the Potential of Generative AI Clinical Case-Based Simulations on Radiography Education: A Pilot Study.Journal of imaging informatics in medicine · 2026Article
- FAD-MIL: a weakly supervised fracture detection model based on X-ray images.Scientific reports · 2026Article
- A machine learning-based predictive model for mandibular third molar extraction difficulty: incorporating multimodal features and SHAP analysis.BMC oral health · 2026Article
- Artificial intelligence-assisted reader evaluation in acute CT head interpretation (AI-REACT): a multireader multicase study.BMJ digital health & AI · 2026Article
- Recent applications of artificial intelligence in cancer radiotherapy and immunotherapy: current status and future directions.Frontiers in immunology · 2026Review
- Applicability and performance of convolutional neural networks for the identification of periodontal bone loss in periapical radiographs: a scoping review.Oral radiology · 2026Article
- Practical applications of AI in body imaging.Abdominal radiology (New York) · 2026Review
- Radiology artificial intelligence for prioritized imaging and diagnosis of lung cancer: qualitative interview analysis of stakeholder perspectives in Northern Ireland.Frontiers in medicine · 2026Article
- AI Integration in Medical Imaging Education: A Nationwide Cross-Sectional Survey.Radiology research and practice · 2026Article
- Perceptions of artificial intelligence for radiographic image accuracy: a cross-sectional survey of radiology personnel.Frontiers in medicine · 2026Article
- Evaluating the role of large language models in supporting patient education during the informed consent process for routine radiology procedures.The British journal of radiology · 2025Article
- Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation.Journal of participatory medicine · 2025Article
- Imaging-pathology correlation in pancreatic cancer: Methodological considerations and future directions.World journal of gastrointestinal oncology · 2025Article
- Knowledge, attitudes, and practices of cardiovascular health care personnel regarding coronary CTA and AI-assisted diagnosis: a cross-sectional study.Journal of global health · 2025Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radiographer role is lacking. This paper discusses the potential impact of artificial intelligence (AI) on the radiography profession by assessing current workflow and cross-mapping potential areas of AI automation such as procedure planning, image acquisition and processing. We also highlight the opportunities that AI brings including enhancing patient-facing care, increased cross-modality education and working, increased technological expertise and expansion of radiographer responsibility into AI-supported image reporting and auditing roles.
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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.