ReviewPediatric radiology2022
How does artificial intelligence in radiology improve efficiency and health outcomes?
Review in Pediatric radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 7 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
108 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Cost-effectiveness of artificial intelligence tools in radiology: a systematic review.European radiology · 2026Pooled it
- Factors influencing AI acceptance in radiology: a systematic review across the radiology workflow.European radiology · 2026Pooled it
- Artificial intelligence in personalized computed tomography dose optimization: a systematic review of techniques and clinical outcomes.Frontiers in medicine · 2026Pooled it
- Systematic review on the impact of deep learning-driven worklist triage on radiology workflow and clinical outcomes.European radiology · 2025Pooled it
- Artificial Intelligence in the Heart of Medicine: A Systematic Approach to Transforming Arrhythmia Care with Intelligent Systems.Current cardiology reviews · 2025Pooled it
- Artificial intelligence in breast ultrasound: a systematic review of research advances.Frontiers in oncology · 2025Pooled it
- [Applications of artificial intelligence in radiology].Radiologie (Heidelberg, Germany) · 2024Pooled it
- Evaluation of standardized DICOM labels assigned by a hybrid AI tool and its impact on radiologists' reading times.European radiology · 2026Article
- Artificial intelligence-enabled pediatric radiology in low-resource settings: addressing resource constraints in the African healthcare system.Pediatric radiology · 2026Review
- Current applications and challenges of artificial intelligence applied to diagnostics in pediatric musculoskeletal imaging.Pediatric radiology · 2026Review
- Artificial intelligence for pediatric fracture detection: impact on diagnostic revisions and patient recall rates in a tertiary emergency setting.BMC emergency medicine · 2026Article
- Policy analysis and expert consultation on cross-border telehealth services.Bulletin of the World Health Organization · 2026Article
- Artificial Intelligence Across the Radiology Workflow: A Nine-Stage Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Patient Perspectives on Trust in Artificial Intelligence-Powered Tools in Prostate Cancer Diagnostics.Qualitative health research · 2026Article
- Anticipating Moral and Economic Considerations, Opportunities, and Potential Frictions for AI in Medical Imaging: Multistakeholder Cocreation Study.Journal of medical Internet research · 2026Article
- Gaps in artificial intelligence research for rural health in the United States: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- How Do Radiologists Currently Monitor AI in Radiology and What Challenges Do They Face? An Interview Study and Qualitative Analysis.Journal of imaging informatics in medicine · 2026Article
- Large-Scale Foundation Models for Radiological Image Analysis: Clinical Applications, Technical Challenges, and Future Directions.Journal of imaging informatics in medicine · 2026Review
- Blind spots in artificial intelligence systems: poor identification of self-generated medical images-evidence-based cross-sectional study.Frontiers in medicine · 2026Article
- Practical applications of AI in body imaging.Abdominal radiology (New York) · 2026Review
48 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since the introduction of artificial intelligence (AI) in radiology, the promise has been that it will improve health care and reduce costs. Has AI been able to fulfill that promise? We describe six clinical objectives that can be supported by AI: a more efficient workflow, shortened reading time, a reduction of dose and contrast agents, earlier detection of disease, improved diagnostic accuracy and more personalized diagnostics. We provide examples of use cases including the available scientific evidence for its impact based on a hierarchical model of efficacy. We conclude that the market is still maturing and little is known about the contribution of AI to clinical practice. More real-world monitoring of AI in clinical practice is expected to aid in determining the value of AI and making informed decisions on development, procurement and reimbursement.
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.