Spinal cord injury: who works on it

One card per institution. Filter by target, by country, or show only institutions in EU-13 (Horizon Europe widening) countries.

• All targets
• TREM2 0
• GLP-1 1
• NRF2 0
• BDNF 0
• mTOR 0
• NLRP3 0
• SIRT1 0
• STING 0

EU-13 is a filter, not a ranking: it only narrows the list.

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Trials whose registry record says individual participant data (IPD) will be shared.

• Glycemic and Weight Loss Effects of GLP-1R Agonist Therapy in Subjects With Spinal Cord Injury and Type 2 Diabetes

  NCT06706284· Marzieh Salehi· Source

Find publications on this disease by a MeSH method term, for example a sequencing or imaging method.

• Single-Cell Analysis 6
• Organoids 10
• Gene Expression Profiling 25
• Sequence Analysis, RNA 2
• Proteomics 10
• Metabolomics 3
• Flow Cytometry 1
• Immunohistochemistry 27
• Liquid Biopsy 1
• Positron-Emission Tomography 4
• Magnetic Resonance Imaging 116
• Machine Learning 27
• Deep Learning 9
• Cohort Studies 58
• Genome-Wide Association Study 2

• RMAF: A deep learning-based framework for automatic assessment of spinal cord injured rats locomotor performance using the horizontal ladder test.

  Behav Brain Res, Jul 2026

• [Value of a deep learning-based visual model for predicting postoperative upper limb functional recovery after severe acute cervical spinal cord injury].

  Zhonghua Yi Xue Za Zhi, Jun 2026

• Automated segmentation of neurons and spinal cord structures in immunofluorescence images using SpineDL.

  Sci Rep, Jun 2026

• Development and multi-institutional validation of a deep learning algorithm for predicting cervical cord compression using dynamic cervical lateral radiographs.

  Sci Rep, Jun 2026

• Performance comparison between a deep learning model and spine surgeons in detecting cervical spinal cord compression on radiographs.

  J Neurosurg Spine, May 2026

• Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats.

  J Vis Exp, Apr 2026

• MedFusion-gP-AKI: development and multicenter validation of a machine learning fusion model for early prediction of KDIGO stage 3 acute kidney injury in critically ill traumatic cervicothoracic spinal cord injury patients.

  Ren Fail, Mar 2026

• Automated Detection of Cervical Spinal Cord Compression on MRI Using YOLO11 Deep Learning Architecture: A Two-Center External Validation Study.

  Spine (Phila Pa 1976), Feb 2026

• Spinal Cord Segmentation and Injury Detection based on Siamese Conventional WideRes Network using CT Image.

  Eur Spine J, Nov 2025

See which targets of this disease your abstract mentions, and go to the people working on them.