SynthesisEuropean radiology2021
Training opportunities of artificial intelligence (AI) in radiology: a systematic review.
Synthesis in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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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
27 citing papers in PubMed.
- Role-Differentiated AI Competencies and Curriculum Implications for Health Professions Education: Qualitative Study.JMIR medical education · 2026Article
- Teaching AI for Radiology Applications: a Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM.Journal of imaging informatics in medicine · 2026Article
- Exploring the use of AI-generated counterfactual chest X-rays to enhance diagnostic learning in medical education.BMC medical education · 2026Article
- Investigating the Potential of Generative AI Clinical Case-Based Simulations on Radiography Education: A Pilot Study.Journal of imaging informatics in medicine · 2026Article
- Application of an AI-enhanced interactive virtual clinical reasoning training system in orthodontic residency training.Frontiers in medicine · 2026Article
- Teaching AI for Radiology Applications: A Multisociety‑Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM.Medical physics · 2025Article
- AI Revolution in Radiology, Radiation Oncology and Nuclear Medicine: Transforming and Innovating the Radiological Sciences.Journal of medical imaging and radiation oncology · 2025Review
- Perception and Understanding of Artificial Intelligence Among Gastroenterology Fellows and Early Career Gastroenterologists: A Nationwide Cross-Sectional Survey Study.Digestive diseases and sciences · 2025Article
- AI-driven healthcare innovations for enhancing clinical services during mass gatherings (Hajj): task force insights and future directions.BMC health services research · 2025Article
- Evaluating a clinically available artificial intelligence model for intracranial aneurysm detection: a multi-reader study and algorithmic audit.Neuroradiology · 2025Article
- Enhancing medical imaging education: integrating computing technologies, digital image processing and artificial intelligence.Journal of medical radiation sciences · 2025Article
- Emerging technologies in pediatric radiology: current developments and future prospects.Pediatric radiology · 2024Review
- Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts.Radiology. Artificial intelligence · 2024Article
- A framework to integrate artificial intelligence training into radiology residency programs: preparing the future radiologist.Insights into imaging · 2024Article
- Radiologic Technology Students' Perceptions on Adoption of Artificial Intelligence Technology in Radiology.International journal of general medicine · 2024Article
- Artificial intelligence in rheumatology: status quo and quo vadis-results of a national survey among German rheumatologists.Therapeutic advances in musculoskeletal disease · 2024Article
- Are Advanced Clinical Practitioners perfectly placed to re-report neuroimages to support clinical diagnosis of dementia?International journal for advancing practice · 2023Article
- Article
- Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study.Insights into imaging · 2023Article
- Artificial-Intelligence-Aided Radiographic Diagnostic of Knee Osteoarthritis Leads to a Higher Association of Clinical Findings with Diagnostic Ratings.Journal of clinical medicine · 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe aim is to offer an overview of the existing training programs and critically examine them and suggest avenues for further development of AI training programs for radiologists.
methodsDeductive thematic analysis of 100 training programs offered in 2019 and 2020 (until June 30). We analyze the public data about the training programs based on their "contents," "target audience," "instructors and offering agents," and "legitimization strategies."
resultsThere are many AI training programs offered to radiologists, yet most of them (80%) are short, stand-alone sessions, which are not part of a longer-term learning trajectory. The training programs mainly (around 85%) focus on the basic concepts of AI and are offered in passive mode. Professional institutions and commercial companies are active in offering the programs (91%), though academic institutes are limitedly involved.
conclusionsThere is a need to further develop systematic training programs that are pedagogically integrated into radiology curriculum. Future training programs need to further focus on learning how to work with AI at work and be further specialized and customized to the contexts of radiology work. KEY POINTS: • Most of AI training programs are short, stand-alone sessions, which focus on the basics of AI. • The content of training programs focuses on medical and technical topics; managerial, legal, and ethical topics are marginally addressed. • Professional institutions and commercial companies are active in offering AI training; academic institutes are limitedly involved.
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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.