ReviewThe British journal of radiology2019
Artificial intelligence for precision education in radiology.
Review in The British journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 2 of them syntheses 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.
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Who cites it
87 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- AI demonstrates comparable diagnostic performance to radiologists in MRI detection of anterior cruciate ligament tears: a systematic review and meta-analysis.European radiology · 2026Pooled it
- Use of artificial intelligence in education and training of radiology.Frontiers in radiology · 2026Pooled it
- AI-Empowered Nuclear Medicine Education, Part 1: Theoretical and Ethical Foundation.Journal of nuclear medicine technology · 2026Article
- Awareness and perceptions of artificial intelligence among pulmonologists and thoracic surgeons: a national survey.Journal of cardiothoracic surgery · 2026Article
- PatchChestCT: A patch-level spatial annotation dataset for nine abnormalities in chest CT.Scientific data · 2026Article
- From volume to value: leveraging artificial intelligence and deliberate practice to foster precision learning in radiology.Pediatric radiology · 2026Review
- Integrating Artificial Intelligence into Prostate MR Imaging: Technical Foundations, Clinical Applications, and Workflow Implications.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Review
- Exploring the use of AI-generated counterfactual chest X-rays to enhance diagnostic learning in medical education.BMC medical education · 2026Article
- Fill the VOID- an introductory guide for learning medical imaging.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
- Differential Diagnosis of Parotid Tumors on Ultrasound: Interobserver Variability and Examiner-Specific Decision Rules-A Machine Learning Approach.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial intelligence-assisted training for rib fracture interpretation: a prospective study in undergraduate medical students.World journal of emergency surgery : WJES · 2026Observational
- Recent advances in artificial intelligence-assisted medical imaging education.Frontiers in medicine · 2026Review
- RadCLARE: an automated clinical language engine for detecting semantic errors in radiology reports.European radiology experimental · 2025Article
- Artificial Intelligence in Radiology: Advancing Precision, Accuracy, and Early Detection in Cancer Diagnosis.Cureus · 2025Review
- The use of artificial intelligence in paediatric postgraduate medical education: A scoping review.Paediatrics & child health · 2025Article
- Revolutionizing radiology education: exploring innovative teaching methods.Abdominal radiology (New York) · 2025Review
- A deep learning framework for automated dental segmentation and diagnostic report generation from cone-beam computed tomography.Head & face medicine · 2025Article
- AI as teacher: effectiveness of an AI-based training module to improve trainee pediatric fracture detection.Skeletal radiology · 2025Article
- Artificial Intelligence for Teaching Case Curation: Evaluating Model Performance on Imaging Report Discrepancies.Academic radiology · 2025Article
27 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
Abstract
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about AI, here our goal is to instead focus on how AI might be developed to better teach radiology trainees. While the idea of using AI to improve education is not new, the application of AI to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an AI-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of "AI-augmented radiology" may enable not only "precision medicine" but also what we describe as "precision medical education," where instruction is tailored to individual trainees based on their learning styles and needs.
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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.