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Specialty: Neurology
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Total 1309 results found since Jan 2013.
Prediction of Motor Outcome of Stroke Patients Using a Deep Learning Algorithm with Brain MRI as Input Data
Conclusion: We showed that a CNN model trained using whole-brain axial T2-weighted MR images of stroke patients would help predict upper and lower limb motor function at the chronic stage.Eur Neurol
Source: European Neurology - June 23, 2022 Category: Neurology Source Type: research
Circulating Plasma miRNA Homologs in Mice and Humans Reflect Familial Cerebral Cavernous Malformation Disease
AbstractPatients with familial cerebral cavernous malformation (CCM) inherit germline loss of function mutations and are susceptible to progressive development of brain lesions and neurological sequelae during their lifetime. To date, no homologous circulating molecules have been identified that can reflect the presence of germ line pathogenetic CCM mutations, either in animal models or patients. We hypothesize that homologous differentially expressed (DE) plasma miRNAs can reflect the CCM germline mutation in preclinical murine models and patients. Herein, homologous DE plasma miRNAs with mechanistic putative gene targets...
Source: Translational Stroke Research - June 17, 2022 Category: Neurology Source Type: research
Machine Learning-Based Model for Prediction of Hemorrhage Transformation in Acute Ischemic Stroke After Alteplase
In this study, an RF machine learning method was successfully established to predict HT in AIS patients after intravenous alteplase, which the sensitivity was 66.7%, and the specificity was 80.7%.
Source: Frontiers in Neurology - June 10, 2022 Category: Neurology Source Type: research
Machine Learning –Based Identification of Target Groups for Thrombectomy in Acute Stroke
AbstractWhether endovascular thrombectomy (EVT) improves functional outcome in patients with large-vessel occlusion (LVO) stroke that do not comply with inclusion criteria of randomized controlled trials (RCTs) but that are considered for EVT in clinical practice is uncertain. We aimed to systematically identify patients with LVO stroke underrepresented in RCTs who might benefit from EVT. Following the premises that (i) patients without reperfusion after EVT represent a non-treated control group and (ii) the level of reperfusion affects outcome in patients with benefit from EVT but not in patients without treatment benefit...
Source: Translational Stroke Research - June 7, 2022 Category: Neurology Source Type: research
Direct AT2R Stimulation Slows Post-stroke Cognitive Decline in the 5XFAD Alzheimer ’s Disease Mice
AbstractAlzheimer ’s disease (AD), currently the single leading cause of death still on the rise, almost always coexists alongside vascular cognitive impairment (VCI). In fact, the ischemic disease affects up to 90% of AD patients, with strokes and major infarctions representing over a third of vascular lesions. St udies also confirmed that amyloid plaques, typical of AD, are much more likely to cause dementia if strokes or cerebrovascular damage also exist, leading to the term “mixed pathology” cognitive impairment. Although its incidence is expected to grow, there are no satisfactory treatments. There is hence an u...
Source: Molecular Neurobiology - June 5, 2022 Category: Neurology Source Type: research
“I Give It Everything for an Hour Then I Sleep for Four.” The Experience of Post-stroke Fatigue During Outpatient Rehabilitation Including the Perspectives of Carers: A Qualitative Study
ConclusionDespite engaging in outpatient rehabilitation, stroke survivors largely learnt to manage fatigue independent of healthcare professionals. Carers often facilitated learning, monitoring rehabilitation, daily routines and fatigue exacerbation. Conversely, family could be dismissive of fatigue and possess unrealistic expectations. Post-stroke fatigue must be considered by clinicians when delivering outpatient rehabilitation to stroke survivors. Clinicians should consistently screen for fatigue, provide flexible session scheduling, and educate about individual indicators and strategies for management. Clinicians shoul...
Source: Frontiers in Neurology - June 2, 2022 Category: Neurology 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 - June 1, 2022 Category: Neurology Source Type: research
Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study
We aimed to develop and validate machine learning (ML) models for 30-day stroke mortality for mortality risk stratification and as benchmarking models for quality improvement in stroke care.
Source: BMC Neurology - May 27, 2022 Category: Neurology Authors: Wenjuan Wang, Anthony G. Rudd, Yanzhong Wang, Vasa Curcin, Charles D. Wolfe, Niels Peek and Benjamin Bray Tags: Research Source Type: research
Comparing Poor and Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy in Acute Ischemic Stroke
ConclusionsOur results suggest that a prediction of poor outcome after AIS and MT could be made based on clinical baseline variables only. Speed and extent of MT did improve prediction for a favorable outcome but is not relevant for poor outcome. An MR mismatch with small ischemic core and larger penumbral tissue showed no predictive importance.
Source: Frontiers in Neurology - May 27, 2022 Category: Neurology Source Type: research
A Deep Learning-Based Automatic Collateral Assessment in Patients with Acute Ischemic Stroke
This study aimed to develop a supervised deep learning (DL) model for grading collateral status from dynamic susceptibility contrast magnetic resonance perfusion (DSC-MRP) images from patients with large vessel occlusion (LVO) acute ischemic stroke (AIS) and compare its performance against experts ’ manual grading. Among consecutive LVO-AIS at three medical center sites, DSC-MRP data were processed to generate collateral flow maps consisting of arterial, capillary, and venous phases. With the use of expert readings as a reference, a DL model was developed to analyze collateral status with o utput classified into good and...
Source: Translational Stroke Research - May 21, 2022 Category: Neurology Source Type: research
Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction
ConclusionMachine learning that is applied to quantifiable image features from CT and CTA alongside basic clinical characteristics constitutes a promising automated method in the pre-interventional prediction of stroke prognosis. Interpretable models allow for exploring which initial features contribute the most to post-thrombectomy outcome prediction overall and for each individual patient outcome.
Source: Frontiers in Neurology - May 19, 2022 Category: Neurology Source Type: research
The FAST VAN for Field Identification of Large Vessel Occlusion in Acute Stroke
DISCUSSION: The FAST VAN tool for identification of LVO meets desired characteristics of an effective screening tool in ease of use, efficiency, and accuracy. Aphasia remains the most challenging cortical feature to identify accurately.PMID:35581931 | DOI:10.1017/cjn.2022.32
Source: The Canadian Journal of Neurological Sciences - May 18, 2022 Category: Neurology Authors: Sanchea Wasyliw Ruth Whelan Kim Davy Michael E Kelly Brett Graham Layla Gould Gary Hunter Source Type: research
