ArticleInsights into imaging2024
Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA.
Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluating the impact of the Radiomics Quality Score: a systematic review and meta-analysis.European radiology · 2025Pooled it
- A Multi-Model, Pixel-Native Framework for Automated Computed Tomography Series Labeling and Characterization: Proof-of-Concept Study.JMIR medical informatics · 2026Article
- Human-AI interaction and collaboration in radiology: from conceptual frameworks to responsible implementation.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Review
- Implementation of an artificial intelligence-based system for mammography in the compulsory medical insurance program: results of a 3-year study.Quantitative imaging in medicine and surgery · 2026Article
- Radiological Confirmation of Enteral Feeding Tube Placement Before Initiating Enteral Nutrition: A Review.Cureus · 2026Review
- AI performance varies considerably across mammography devices: a multi-site and multi-vendor retrospective study.Insights into imaging · 2026Article
- Small lesion-high risk: diagnostic performance of artificial intelligence in paediatric fractures with medicolegal impact.Pediatric radiology · 2026Article
- Artificial intelligence as medical device in radiology in 2025: the regulatory scenario in the EU, USA, and China.European radiology · 2026Review
- Uncertainty quantification for artificial intelligence in medical imaging: what every radiologist needs to know.Abdominal radiology (New York) · 2026Review
- Towards an accessible, centralised, searchable database for AI courses in Europe: the Artificial Intelligence in Medical Imaging and Radiation Oncology Education (AIMIROE) project.European radiology experimental · 2026Article
- Eye-Tracking Evidence That Verifiable Explanations Support Visual Evidence Checking in AI-Assisted Chest Radiograph Interpretation.Journal of eye movement research · 2026Article
- From Artificial Intelligence to Robotics: How to Navigate Technological Innovation in Radiology With the Gartner Hype Cycle.Academic radiology · 2026Review
- Vendors' perspectives on AI implementation in medical imaging and oncology: a cross-sectional survey.European radiology · 2026Article
- Anticipating Moral and Economic Considerations, Opportunities, and Potential Frictions for AI in Medical Imaging: Multistakeholder Cocreation Study.Journal of medical Internet research · 2026Article
- Advancing Label-Free Imaging Through CARS Microscopy: From Signal Formation to Biological Interpretation.International journal of molecular sciences · 2026Review
- Artificial Intelligence in Radiology: Hidden Fragilities and the Path to Resilience.Saudi medical journal · 2026Review
- The application of deep neural networks to the detection of lumbar hernias: results from the approaches based on convolutional networks and transformers.Frontiers in radiology · 2026Article
- Mind the gap: challenges and future directions for content-based image retrieval in clinical radiology.Frontiers in radiology · 2026Article
- From scanner to scalpel: adapting IDEAL for accountable AI in radiology and image-guided neurosurgery.Frontiers in radiology · 2026Article
- Over-detection and over-surveillance in breast screening: current status and the potential for artificial intelligence optimisation.Insights into imaging · 2025Review
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever-growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones.This multi-society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools.Key points • The incorporation of artificial intelligence (AI) in radiological practice demands increased monitoring of its utility and safety.• Cooperation between developers, clinicians, and regulators will allow all involved to address ethical issues and monitor AI performance.• AI can fulfil its promise to advance patient well-being if all steps from development to integration in healthcare are rigorously evaluated.
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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.