ArticleFrontiers in neurology2021
Identification and Therapeutic Outcome Prediction of Cervical Spondylotic Myelopathy Based on the Functional Connectivity From Resting-State Functional MRI Data: A Preliminary Machine Learning Study.
Article in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Machine Learning and Deep Learning for the Diagnosis of Cervical Degenerative Diseases: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Brain MRI changes in degenerative cervical myelopathy: a systematic review.EBioMedicine · 2024Pooled it
- Artificial intelligence and machine learning based predictive analytics in cervical myelopathy - a scoping review.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
- Hotspots and Trends in the Application of Artificial Intelligence in Spine Medicine from 2005 to 2024: A Bibliometric and Visualization Analysis.Indian journal of orthopaedics · 2026Article
- Increased cervical spinal cord signal intensity corresponds to specific cerebellar and cerebral functional changes in degenerative cervical myelopathy patients.Scientific reports · 2026Article
- Changes to Dorsal Thalamic Metabolites and Thalamocortical Tract Fiber Injury in Patients with Cervical Spondylotic Myelopathy.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Resting-state brain plasticity is associated with the severity in cervical spondylotic myelopathy.BMC musculoskeletal disorders · 2024Article
- Resting-state functional magnetic resonance imaging indices are related to electrophysiological dysfunction in degenerative cervical myelopathy.Scientific reports · 2024Article
- Intra- and inter-network connectivity abnormalities associated with surgical outcomes in degenerative cervical myelopathy patients: a resting-state fMRI study.Frontiers in neurology · 2024Article
- The role of neuronal plasticity in cervical spondylotic myelopathy surgery: functional assessment and prognostic implication.Neurosurgical review · 2023Review
- Clinical and Research MRI Techniques for Assessing Spinal Cord Integrity in Degenerative Cervical Myelopathy-A Scoping Review.Biomedicines · 2022Article
- Brain Structural and Functional Dissociated Patterns in Degenerative Cervical Myelopathy: A Case-Controlled Retrospective Resting-State fMRI Study.Frontiers in neurology · 2022Article
- Identification of radiographic characteristics associated with pain in hallux valgus patients: A preliminary machine learning study.Frontiers in public health · 2022Article
- Brain connectivity markers in degenerative cervical myelopathy patients with depression for predicting the prognosis following decompression surgery.Frontiers in neurology · 2022Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Currently, strategies to diagnose patients and predict neurological recovery in cervical spondylotic myelopathy (CSM) using MR images of the cervical spine are urgently required. In light of this, this study aimed at exploring potential preoperative brain biomarkers that can be used to diagnose and predict neurological recovery in CSM patients using functional connectivity (FC) analysis of a resting-state functional MRI (rs-fMRI) data. Two independent datasets, including total of 53 patients with CSM and 47 age- and sex-matched healthy controls (HCs), underwent the preoperative rs-fMRI procedure. The FC was calculated from the automated anatomical labeling (AAL) template and used as features for machine learning analysis. After that, three analyses were used, namely, the classification of CSM patients from healthy adults using the support vector machine (SVM) within and across datasets, the prediction of preoperative neurological function in CSM patients
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