ReviewSpine deformity2024
Applications of artificial intelligence for adolescent idiopathic scoliosis: mapping the evidence.
Review in Spine deformity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis 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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A comprehensive narrative review of scoliosis in children and adolescents: epidemiology, screening strategies, therapeutic interventions, and biomechanical research.Frontiers in pediatrics · 2026Pooled it
- The S1-LIV angle is essential for fusion selection in thoracic adolescent idiopathic scoliosis - a dual-center machine learning study with external validation.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- State-of-the-art review in AI and digital technologies for spine deformity.Spine deformity · 2026Review
- From Algorithms to Clinics: Recent Progress in AI for Scoliosis Diagnosis and Management.Journal of clinical medicine · 2026Review
- Principles Underlying Surgical Decision-Making in Lowest-Instrumented Vertebra Level Selection of Adolescent Idiopathic Scoliosis: From Traditional Landmarks to Emerging Predictive Models-A Narrative Review.Journal of clinical medicine · 2026Review
- Radiation-free Cobb angle estimation in adolescent scoliosis using surface topography and a linear regression model.Spine deformity · 2026Article
- VerteRo: A Fully Automated Deep Neural Network Tool for Estimating Axial Vertebral Body Rotation in Adolescent Idiopathic Scoliosis.Global spine journal · 2026Article
- Applications of Artificial Intelligence in Pediatric Orthopaedics.Indian journal of orthopaedics · 2026Review
- Artificial intelligence in early onset scoliosis: a scoping review.Spine deformity · 2026Article
- From routine full-spine radiographs to decision-oriented Risser stratification: an interpretable deep-learning approach.Frontiers in pediatrics · 2026Article
- The role of artificial intelligence in advancing scoliosis care: a rapid review of current evidence and future opportunities.Frontiers in medicine · 2026Review
- Reliability of Large Language Model-Based Artificial Intelligence in AIS Assessment: Lenke Classification and Fusion-Level Suggestion.Diagnostics (Basel, Switzerland) · 2025Article
- AI in Pediatric Spine Care: Clinical, Research, and Ethical Considerations.Journal of clinical medicine · 2025Article
- Development and Validation of Transformer- and Convolutional Neural Network-Based Deep Learning Models to Predict Curve Progression in Adolescent Idiopathic Scoliosis.Journal of clinical medicine · 2025Article
- Revolutionizing spine surgery with emerging AI-FEA integration.Journal of robotic surgery · 2025Review
- Multimodal machine learning for risk-stratified bundled payments in spinal surgery.NPJ digital medicine · 2025Article
- Clinical Failure of General-Purpose AI in Photographic Scoliosis Assessment: A Diagnostic Accuracy Study.Medicina (Kaunas, Lithuania) · 2025Article
- Letter to the editor: re-evaluating approaches: current issues in the treatment of adolescent idiopathic scoliosis.Asian spine journal · 2024Article
- Current issues in the treatment of adolescent idiopathic scoliosis: a comprehensive narrative review.Asian spine journal · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeAdolescent idiopathic scoliosis (AIS) is a common spinal deformity with varying progression, complicating treatment decisions. Artificial intelligence (AI) and machine learning (ML) are increasingly prominent in orthopedic care, aiding in diagnosis, risk-stratification, and treatment guidance. This scoping review outlines AI applications in AIS.
methodsThis study followed PRISMA-ScR guidelines and included articles that reported the development, use, or validation of AI models for treating, diagnosing, or predicting clinical outcomes in AIS.
results40 full-text articles were included, with most studies published in the last 5 years (77.5%). Common ML techniques were convolutional neural networks (55%), decision trees and random forests (15%), and artificial neural networks (15%). Most AI applications in AIS were for imaging analysis (25/40; 62.5%), focusing on automatic measurement of Cobb angle, and axial vertebral rotation (13/25; 52%) and curve classification/severity (13/25; 52%). Prediction was the second most common application (15/40; 37.5%), with studies predicting curve progression (9/15; 60%), and Cobb angles (9/15; 60%). Only 15 studies (37.5%) reported clinical implementation guidelines for AI in AIS management. 52.5% of studies reported model accuracy, with an average of 85.4%.
conclusionThis review highlights the applications of AI in AIS care, notably including automatic radiographic analysis, curve type classification, prediction of curve progression, and AIS diagnosis. However, the current lack of clear clinical implementation guidelines, model transparency, and external validation of studied models limits clinician trust and the generalizability and applicability of AI in AIS management.
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.