Browse the latest research summaries in the field of bioinformatics for spinal cord injury patients and caregivers.
Showing 101-110 of 334 results
Front. Neurosci., 2024 • April 18, 2024
This study introduces a Transformer neural network model with the addition of MoE layer and ProbSparse self-attention mechanism for classifying the time-frequency spatial domain features of MI-EEG dat...
KEY FINDING: EMPT achieves an accuracy of 95.24% on the MI EEG dataset for patients with spinal cord injury.
Journal of Cachexia, Sarcopenia and Muscle, 2024 • May 19, 2024
This study investigates the time course of molecular changes in rat soleus muscle following severe spinal cord injury (SCI) to identify therapeutic targets and windows for treating muscle wasting. The...
KEY FINDING: SCI induces early and transient expression of extracellular matrix (ECM) remodeling genes, leading to muscle fibrosis.
Medicine, 2024 • June 14, 2024
This retrospective study aimed to predict gait function at discharge from an acute inpatient rehabilitation facility following SCI using a ML algorithm. The study demonstrated that ML models can accur...
KEY FINDING: Machine learning can accurately predict gait recovery after SCI.
Frontiers in Genetics, 2024 • June 4, 2024
In this research, we designed and developed a machine learning-based predictive model, ScnML, for predicting spinal cord nerve cell subpopulations. ScnML addresses the computational inefficiencies and ...
KEY FINDING: The prediction performance of ScnML was evaluated on the training dataset with an accuracy of 94.33%.
PLoS Computational Biology, 2024 • July 1, 2024
This study developed a computational model of the neural circuit of micturition to replicate normal bladder function, dysfunction after SCI, and responses to transcutaneous magnetic stimulation (TMS)....
KEY FINDING: The model reproduced the re-emergence of a spinal voiding reflex after SCI, which is typically suppressed in adults but can reappear due to neural reorganization.
CNS Neurosci Ther, 2024 • June 18, 2024
This study aimed to confirm the inhibitory effect of nicotinamide on fibrotic scar formation following spinal cord injury (SCI) in mice using functional metabolomics. The researchers employed a novel ...
KEY FINDING: Nicotinamide (NAM) administration led to a reduction in fibrotic lesion area following spinal cord injury in mice.
Scientific Reports, 2024 • June 24, 2024
This study introduces a nested ensemble algorithm to predict motor function recovery in TCSCI patients using early ASIA motor scores. The algorithm combines multiple machine learning models in two sta...
KEY FINDING: The nested ensemble algorithm achieved an accuracy of 80.6% and an F1 score of 80.6% in predicting motor function recovery after TCSCI.
J. Clin. Med., 2024 • August 1, 2024
This study assessed the feasibility of predicting daily living ability (SCIM Score) at discharge from rehabilitation using demographic and clinical data from a large single-center database of individu...
KEY FINDING: Both ANN and linear regression models identified key predictors of functional outcomes, such as age, injury level, and initial SCIM scores.
Journal of Neuroinflammation, 2024 • August 22, 2024
This study aimed to explore the roles of oligodendrocytes and their interactions with other glial cells in neuropathic pain (NP) development using a chronic constriction injury (CCI) model in mice and...
KEY FINDING: Neuropathic pain peaked on day 7 after chronic constriction injury in mice, concurrent with myelin lesions in both the spinal cord and sciatic nerve.
Heliyon, 2024 • August 13, 2024
This study addresses the problem of making rehabilitation program decisions for spinal cord injury (SCI) patients using electronic medical records (EMRs). An improved MLSMOTE multi-label learning fram...
KEY FINDING: The improved MLSMOTE multi-label learning framework effectively addresses the class imbalance problem in EMR data.