ReviewPediatric radiology2022
Current and emerging artificial intelligence applications for pediatric musculoskeletal radiology.
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 32 papers.
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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.
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Who cites it
32 citing papers in PubMed.
- Multivendor comparison study of artificial intelligence software for automated fracture detection in paediatric patients.Pediatric radiology · 2026Article
- Current applications and challenges of artificial intelligence applied to diagnostics in pediatric musculoskeletal imaging.Pediatric radiology · 2026Review
- Artificial Intelligence in Pediatric Imaging: A Primer for Pediatric Clinicians.Indian journal of pediatrics · 2026Review
- The current state of artificial intelligence research in pediatric radiology and recommendations for the future: a scoping review.Pediatric radiology · 2026Article
- Artificial intelligence-enabled pediatric radiology in low-resource settings: addressing resource constraints in the African healthcare system.Pediatric radiology · 2026Review
- Artificial intelligence and pediatric imaging data: ethical strategies for learning and collaboration.Pediatric radiology · 2026Review
- Pediatric fracture classification in plain radiographs using EfficientNetV2 with proximal policy optimization fine-tuning.Scientific reports · 2026Article
- Developing new methods for the accurate evaluation of children's bone age based on X-ray images: a study on the accuracy and consistency of artificial intelligence and manual bone age evaluation.Quantitative imaging in medicine and surgery · 2026Article
- Performance of a deep learning-based algorithm for automated measurements of Cobb angles on preoperative spine radiographs in adolescent idiopathic scoliosis.Pediatric radiology · 2026Article
- [Skeletal dysplasias-Multidisciplinary orthopedics].Orthopadie (Heidelberg, Germany) · 2025Review
- Population-specific calibration and validation of an open-source bone age AI.Scientific reports · 2025Article
- The Impact of Artificial Intelligence on Radiologists' Reading Time in Bone Age Radiograph Assessment: A Preliminary Retrospective Observational Study.Journal of imaging informatics in medicine · 2025Observational
- Current and Emerging Applications of Artificial Intelligence in Medical Imaging for Paediatric Hip Disorders-A Scoping Review.Children (Basel, Switzerland) · 2025Review
- Use of deep learning model for paediatric elbow radiograph binomial classification: initial experience, performance and lessons learnt.Singapore medical journal · 2025Article
- Some artificial intelligence tools may currently be useful in orthopedic surgery and traumatology.World journal of orthopedics · 2025Article
- Comparison of bone age assessment using manual Greulich and Pyle method versus automated BoneXpert method in South African children.SA journal of radiology · 2025Article
- Artificial intelligence model system for bone age assessment of preschool children.Pediatric research · 2024Article
- Artificial intelligence awareness and perceptions among pediatric orthopedic surgeons: A cross-sectional observational study.World journal of orthopedics · 2024Article
- Bone health in childhood low-grade glioma: an understudied problem.Endocrine connections · 2024Article
- Emerging technologies in pediatric radiology: current developments and future prospects.Pediatric radiology · 2024Review
Corrections and comments
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Authors and funding
1 author.
Funding
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Abstract
Artificial intelligence (AI) is playing an ever-increasing role in radiology (more so in the adult world than in pediatrics), to the extent that there are unfounded fears it will completely take over the role of the radiologist. In relation to musculoskeletal applications of AI in pediatric radiology, we are far from the time when AI will replace radiologists; even for the commonest application (bone age assessment), AI is more often employed in an AI-assist mode rather than an AI-replace or AI-extend mode. AI for bone age assessment has been in clinical use for more than a decade and is the area in which most research has been conducted. Most other potential indications in children (such as appendicular and vertebral fracture detection) remain largely in the research domain. This article reviews the areas in which AI is most prominent in relation to the pediatric musculoskeletal system, briefly summarizing the current literature and highlighting areas for future research. Pediatric radiologists are encouraged to participate as members of the research teams conducting pediatric radiology artificial intelligence research.
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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.