ReviewSpine deformity2026
Digital twins and multimodal artificial intelligence in spine care: a scoping review of concepts, evidence, and translational barriers.
Review in Spine deformity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction models for curve progression in adolescent idiopathic scoliosis: a systematic review with exploratory meta-analysis of discrimination.BMC musculoskeletal disorders · 2026Pooled it
- Response to Comment on "Emergency Department Predictors of Mechanical Ventilation in Pediatric Spine Fracture Patients in the US".Global spine journal · 2026Article
- Neuroimmune Phenotyping as the Next Frontier in Chronic Pain Medicine for Musculoskeletal Back Pain.Current pain and headache reports · 2026Review
- AI parameters for enhancing spine surgery outcomes: a narrative review.Journal of spine surgery (Hong Kong) · 2026Review
- Large Language Models in Spine Surgery: A Scoping Review of Clinical Efficacy, Technical Integration, and Ethical Paradigms.Global spine journal · 2026Review
- Ordinal Deep Learning for Lumbar Foraminal Stenosis Grading on Sagittal MRI.Journal of imaging · 2026Article
- Deep Learning-Based Multi-Class Pediatric Wrist Fracture Subtype Classification: A Pilot Study Comparing Convolutional Neural Network Architectures.Journal of imaging · 2026Article
- Response to: Comment on 'Risk prediction in spine surgery: a scoping review of traditional models, artificial intelligence, and the challenge of clinical translation'.Spine deformity · 2026Article
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
purposeThis scoping review examines current evidence supporting multimodal artificial intelligence, continuous monitoring, and digital twin concepts in spine care. Our primary aims were to (1) characterize the state of digital twin development in spine care, (2) identify key technological and conceptual gaps, and (3) evaluate translational barriers to clinical implementation.
methodsA scoping review was conducted following PRISMA-ScR guidelines. PubMed/MEDLINE, Scopus, and Web of Science were searched for studies published between January 2010 and March 2025. Findings were synthesized qualitatively.
resultsTwenty-six studies met inclusion criteria. Existing spine prediction models demonstrate modest discrimination and are predominantly static. Imaging-based AI shows weak associations with pain and disability. Wearable sensor monitoring is feasible but lacks consistent evidence for improved outcomes. Spine-specific digital twins remain conceptual, with no prospective validation demonstrating improved decision-making.
conclusionMultimodal AI-enabled digital twins represent a compelling conceptual framework for personalized spine care, but current evidence does not support clinical superiority or readiness for implementation. Progress will require prospective validation, standardized data integration, and regulatory clarity.
Indexed as
Identifiers
42101555What Socratic 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 Socratic graph.