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Specialty: Neurology
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Total 1309 results found since Jan 2013.
Assessment of the relationship between Val66Met BDNF polymorphism and the effectiveness of gait rehabilitation in children and adolescents with cerebral palsy
Acta Neurobiol Exp (Wars). 2022;82(1):1-11. doi: 10.55782/ane-2022-001.ABSTRACTCerebral palsy (CP) is associated with the non‑progressive damage of upper motor neurons, which is manifested by a variety of symptoms, particularly motor and functional deficits. During the rehabilitation of patients with CP, attention is paid to improving mobility which can have a significant impact on the child's development. The effectiveness of rehabilitation depends on the plasticity of the nervous system, which may be genetically determined. Of importance are the various polymorphisms of the brain derived neurotrophic factor (BDNF) gene...
Source: Acta Neurobiologiae Experimentalis - April 22, 2022 Category: Neurology Authors: Bartosz Bagrowski Marta Czapracka Joanna Kra śny Micha ł Prendecki Jolanta Dorszewska Marek J óźwiak Source Type: research
Machine Learning-Based Perihematomal Tissue Features to Predict Clinical Outcome after Spontaneous Intracerebral Hemorrhage
To explore whether radiomic features of perihematomal tissue can improve the forecasting accuracy for the prognosis of patients with an intracerebral hemorrhage (ICH).
Source: Journal of Stroke and Cerebrovascular Diseases - April 11, 2022 Category: Neurology Authors: Xin Qi, Guorui Hu, Haiyan Sun, Zhigeng Chen, Chao Yang Source Type: research
Correction to: Accuracy and Prognostic Role of NCCT-ASPECTS Depend on Time from Acute Stroke Symptom-onset for both Human and Machine-learning Based Evaluation
Source: Clinical Neuroradiology - April 7, 2022 Category: Neurology Source Type: research
Hospital Length of Stay and 30-Day Mortality Prediction in Stroke: A Machine Learning Analysis of 17,000 ICU Admissions in Brazil
ConclusionsHospital length of stay and 30-day mortality of patients admitted to the ICU with stroke were accurately predicted through machine learning methods, even in the absence of stroke-specific data, such as the National Institutes of Health Stroke Scale score or neuroimaging findings. The proposed methods using general intensive care databases may be used for resource use allocation planning and performance assessment of ICUs treating stroke. More detailed acute neurological and management data, as well as long-term functional outcomes, may improve the accuracy and applicability of future machine-learning-based prediction algorithms.
Source: Neurocritical Care - April 6, 2022 Category: Neurology Source Type: research
Combination of Radiological and Clinical Baseline Data for Outcome Prediction of Patients With an Acute Ischemic Stroke
ConclusionsThe combination of radiomics and deep learning image features with clinical data significantly improved the prediction of good reperfusion. The visualization of prediction feature importance showed both known and novel clinical and imaging features with predictive values.
Source: Frontiers in Neurology - April 1, 2022 Category: Neurology Source Type: research
Functional Connectivity Changes in Multiple-Frequency Bands in Acute Basal Ganglia Ischemic Stroke Patients: A Machine Learning Approach
CONCLUSION: Acute BGIS patients had frequency-specific alterations in FC; SVM is a promising method for exploring these frequency-dependent FC alterations. The abnormal brain regions might be potential targets for future researchers in the rehabilitation and treatment of stroke patients.PMID:35356364 | PMC:PMC8958111 | DOI:10.1155/2022/1560748
Source: Neural Plasticity - March 31, 2022 Category: Neurology Authors: Jie Li Lulu Cheng Shijian Chen Jian Zhang Dongqiang Liu Zhijian Liang Huayun Li Source Type: research
Practical Machine Learning Model to Predict the Recovery of Motor Function in Patients with Stroke
Conclusion: Although we used simple and common data that can be obtained in clinical practice as variables, our DNN algorithm was useful for predicting motor recovery of the upper and lower extremities in stroke patients during the recovery phase.Eur Neurol
Source: European Neurology - March 29, 2022 Category: Neurology Source Type: research
Therapeutic Effect of Repetitive Transcranial Magnetic Stimulation for Post-stroke Vascular Cognitive Impairment: A Prospective Pilot Study
ConclusionsHigh-frequency rTMS on the ipsilesional DLPFC may exert immediate efficacy on cognition with the anti-inflammatory response and changes in brain network in PSCI, lasting at least 3 months.
Source: Frontiers in Neurology - March 22, 2022 Category: Neurology Source Type: research
Bridging the Transient Intraluminal Stroke Preclinical Model to Clinical Practice: From Improved Surgical Procedures to a Workflow of Functional Tests
Acute ischemic stroke (AIS) remains a leading cause of mortality, despite significant advances in therapy (endovascular thrombectomy). Failure in developing novel effective therapies is associated with unsuccessful translation from preclinical studies to clinical practice, associated to inconsistent and highly variable infarct areas and lack of relevant post-stroke functional evaluation in preclinical research. To outreach these limitations, we optimized the intraluminal transient middle cerebral occlusion, a widely used mouse stroke model, in two key parameters, selection of appropriate occlusion filaments and time of occ...
Source: Frontiers in Neurology - March 11, 2022 Category: Neurology Source Type: research
Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability
ConclusionsCAPITAL-CT generated standard and reproducible images that could simplify the work of radiologists, which would be of great help in the follow-up of stroke patients and in multifield research in neuroscience.
Source: Frontiers in Neurology - March 11, 2022 Category: Neurology Source Type: research
Computational Approaches for Acute Traumatic Brain Injury Image Recognition
In recent years, there have been major advances in deep learning algorithms for image recognition in traumatic brain injury (TBI). Interest in this area has increased due to the potential for greater objectivity, reduced interpretation times and, ultimately, higher accuracy. Triage algorithms that can re-order radiological reading queues have been developed, using classification to prioritize exams with suspected critical findings. Localization models move a step further to capture more granular information such as the location and, in some cases, size and subtype, of intracranial hematomas that could aid in neurosurgical ...
Source: Frontiers in Neurology - March 9, 2022 Category: Neurology Source Type: research
