ReviewEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2022
Artificial intelligence and spine imaging: limitations, regulatory issues and future direction.
Review in 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, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 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
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Deep learning assisted segmentation of the lumbar intervertebral disc: a systematic review and meta-analysis.Journal of orthopaedic surgery and research · 2024Pooled it
- Are current machine learning applications comparable to radiologist classification of degenerate and herniated discs and Modic change? A systematic review and meta-analysis.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 · 2023Pooled it
- AI parameters for enhancing spine surgery outcomes: a narrative review.Journal of spine surgery (Hong Kong) · 2026Review
- AI-driven computational drug design: tools, workflow and challenges.RSC advances · 2026Review
- Digital twins and multimodal artificial intelligence in spine care: a scoping review of concepts, evidence, and translational barriers.Spine deformity · 2026Review
- Article
- [Artificial intelligence in spinal surgery: current applications and future perspectives].Orthopadie (Heidelberg, Germany) · 2026Review
- The Perceived Roles of AI in Clinical Practice: National Survey of 941 Academic Physicians.JMIR AI · 2025Article
- Bibliometric and Visualized Analysis of Research Relating to Spinal Modic Changes Reported Over the Period 2004-2024.Orthopaedic surgery · 2025Article
- Spine Trauma Classifications: Historical, Current, and Emerging Perspectives for Radiologists.The Indian journal of radiology & imaging · 2025Review
- Exploring the Biopsychosocial Impact of Chronic Low Back Pain in Workers Through Artificial Intelligence-Driven Phenotyping.JOR spine · 2025Article
- Fully automated pedicle screw manufacturer identification in plain radiograph with deep learning methods.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 · 2025Article
- Application of artificial intelligence in medical imaging for tumor diagnosis and treatment: a comprehensive approach.Discover oncology · 2025Review
- Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network.Journal of orthopaedic surgery and research · 2025Article
- Intra-Examiner Reliability and Validity of Sagittal Cervical Spine Mensuration Methods Using Deep Convolutional Neural Networks.Journal of clinical medicine · 2024Article
- Artificial intelligence-aided lytic spinal bone metastasis classification on CT scans.International journal of computer assisted radiology and surgery · 2023Article
- Revolutionizing Spinal Care: Current Applications and Future Directions of Artificial Intelligence and Machine Learning.Journal of clinical medicine · 2023Review
- Potential Applications of Artificial Intelligence and Machine Learning in Spine Surgery Across the Continuum of Care.International journal of spine surgery · 2023Article
- Synapse-Mimetic Hardware-Implemented Resistive Random-Access Memory for Artificial Neural Network.Sensors (Basel, Switzerland) · 2023Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs big data and artificial intelligence (AI) in spine care, and medicine as a whole, continue to be at the forefront of research, careful consideration to the quality and techniques utilized is necessary. Predictive modeling, data science, and deep analytics have taken center stage. Within that space, AI and machine learning (ML) approaches toward the use of spine imaging have gathered considerable attention in the past decade. Although several benefits of such applications exist, limitations are also present and need to be considered. PURPOSE: The following narrative review presents the current status of AI, in particular, ML, with special regard to imaging studies, in the field of spinal research.
methodsA multi-database assessment of the literature was conducted up to September 1, 2021, that addressed AI as it related to imaging of the spine. Articles written in English were selected and critically assessed.
resultsOverall, the review discussed the limitations, data quality and applications of ML models in the context of spine imaging. In particular, we addressed the data quality and ML algorithms in spine imaging research by describing preliminary results from a widely accessible imaging algorithm that is currently available for spine specialists to reference for information on severity of spine disease and degeneration which ultimately may alter clinical decision-making. In addition, awareness of the current, under-recognized regulation surrounding the execution of ML for spine imaging was raised.
conclusionsRecommendations were provided for conducting high-quality, standardized AI applications for spine imaging.
Indexed as
Identifiers
35084588What 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.