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Predicting futile recanalization, malignant cerebral edema, and cerebral herniation using intelligible ensemble machine learning following mechanical thrombectomy for acute ischemic stroke
ConclusionUsing the ensemble ML model to analyze the clinical and imaging data of AIS patients with successful recanalization at admission and within 24 h after MT allowed for accurately predicting the risks of futile recanalization, MCE, and CH.
Source: Frontiers in Neurology - September 28, 2022 Category: Neurology Source Type: research

Comparison of ischemic stroke diagnosis models based on machine learning
ConclusionThe LASSO, SVM-RFE, and RF models have good prediction abilities. However, the ANN model is efficient at classifying positive samples and is unsuitable at classifying negative samples.
Source: Frontiers in Neurology - December 5, 2022 Category: Neurology Source Type: research

Stroke risk prediction by color Doppler ultrasound of carotid artery-based deep learning using Inception V3 and VGG-16
ConclusionIn this research, we classified color Doppler ultrasound images into high-risk carotid vulnerable and stable carotid plaques. We fine-tuned pre-trained deep learning models to classify color Doppler ultrasound images according to our dataset. Our suggested framework helps prevent incorrect diagnoses caused by low image quality and individual experience, among other factors.
Source: Frontiers in Neurology - February 14, 2023 Category: Neurology Source Type: research

Machine learning segmentation of core and penumbra from acute stroke CT perfusion data
We present an alternative model for the estimation of tissue fate using multiple perfusion measures simultaneously.MethodsWe used machine learning (ML) models based on four different algorithms, combining four CTP measures (cerebral blood flow, cerebral blood volume, mean transit time and delay time) plus 3D-neighborhood (patch) analysis to predict the acute ischemic core and perfusion lesion volumes. The model was developed using 86 patient images, and then tested further on 22 images.ResultsXGBoost was the highest-performing algorithm. With standard threshold-based core and penumbra measures as the reference, the model d...
Source: Frontiers in Neurology - February 23, 2023 Category: Neurology Source Type: research

A brain CT-based approach for predicting and analyzing stroke-associated pneumonia from intracerebral hemorrhage
DiscussionOur findings suggest that our method is effective in classifying the development of pneumonia based on brain CT scans. Furthermore, we identified distinct characteristics, such as volume and distribution, of ICH in four different types of SAP.
Source: Frontiers in Neurology - June 2, 2023 Category: Neurology Source Type: research

Robot-Assisted Therapy in Upper Extremity Hemiparesis: Overview of an Evidence-Based Approach
Conclusion Robotic therapy has matured and represents an embodiment of a paradigm shift in neurorehabilitation following a stroke: instead of focusing on compensation, it affords focus in ameliorating the impaired limb in line with concepts of neuroplasticity. This technology-based treatment provides intensity, interactivity, flexibility, and adaptiveness to patient's performance and needs. Furthermore, it increases the productivity of rehabilitation care. Of course, efficiency must be discussed within a local perspective. For example, following the cost containment shown in the VA ROBOTICS study (46), the UK Nati...
Source: Frontiers in Neurology - April 23, 2019 Category: Neurology Source Type: research

Potential Applications of Remote Limb Ischemic Conditioning for Chronic Cerebral Circulation Insufficiency
Conclusion Due to its long-term and often invisible course, CCCI has received less attention than acute cerebral ischemic stroke. However, without appropriate intervention, CCCI may lead to a variety of adverse events. Because the pathophysiological changes associated with CCCI are complex, pharmacological research in this area has been disappointing. Recent research suggests that RLIC, which is less invasive and more well-tolerated than drug treatment, can activate endogenous protective mechanisms during CCCI. In the present report, we reviewed studies related to CCCI (Table 1), as well as those related to stroke and sta...
Source: Frontiers in Neurology - May 2, 2019 Category: Neurology Source Type: research

A Kinematic Study of Progressive Micrographia in Parkinson's Disease
This study has investigated the kinematic features of progressive micrographia during a repetitive writing task. Twenty-four PD patients with duration since diagnosis of <10 years and 24 age-matched controls wrote the letter “e” repeatedly. PD patients were studied in defined off states, with scoring of motor function on the Unified Parkinson's Disease Rating Scale Part III. A digital tablet captured x-y coordinates and ink-pen pressure. Customized software recorded the data and offline analysis derived the kinematic features of pen-tip movement. The average size of the first and the last fi...
Source: Frontiers in Neurology - April 23, 2019 Category: Neurology Source Type: research

Clinical Risk Score for Predicting Recurrence Following a Cerebral Ischemic Event
Conclusion: The clinical risk scores that currently exist for predicting short-term and long-term risk of recurrent cerebral ischemia are limited in their performance and clinical utilities. There is a need for a better predictive tool which can overcome the limitations of current predictive models. Application of machine learning methods in combination with electronic health records may provide platform for development of new-generation predictive tools.
Source: Frontiers in Neurology - November 11, 2019 Category: Neurology Source Type: research

Modifiable Lifestyle Factors and Cognitive Function in Older People: A Cross-Sectional Observational Study
Conclusions: Lifestyle factors, such as physical activity, sleep, and social activity appear to be associated with cognitive function among older people. Physical activity and appropriate durations of sleep and conversation are important for cognitive function. Introduction Dementia is a major public health issue worldwide, with a serious burden for patients, caregivers, and society, as well as substantial economic impacts (1). Although the prevalence of late-life cognitive impairment and dementia are expected to increase in future, effective disease-modifying treatments are currently unavailable. Therefore, unders...
Source: Frontiers in Neurology - April 23, 2019 Category: Neurology Source Type: research

Knockdown of NRSF Alleviates Ischemic Brain Injury and Microvasculature Defects in Diabetic MCAO Mice
Diabetes is one of the well-established risk factors of stroke and is associated with a poor outcome in patients with stroke. Previous studies have shown that the expression of neuron restrictive silencer factor (NRSF) is elevated in diabetes as well as ischemic stroke. However, the role of NRSF in regulating an outcome of diabetic ischemic stroke has not been completely understood. Here, we hypothesized that diabetes-induced NRSF elevation can aggravate brain injury and cognition impairment in ischemic stroke. The diabetic ischemic stroke mice model was established by 8 weeks of high-fat-diet feeding and 5 days of strepto...
Source: Frontiers in Neurology - May 13, 2022 Category: Neurology Source Type: research

Delirium detection using wearable sensors and machine learning in patients with intracerebral hemorrhage
ConclusionsWe found that actigraphy in conjunction with machine learning models improves clinical detection of delirium in patients with stroke, thus paving the way to make actigraph-assisted predictions clinically actionable.
Source: Frontiers in Neurology - June 9, 2023 Category: Neurology Source Type: research

Machine learning approach for hemorrhagic transformation prediction: Capturing predictors' interaction
ConclusionCerebral microbleeds, NIHSS, and infarction size were identified as HT predictors. The best predicting models were RFC and GBC capable of capturing nonlinear interaction between predictors. Predictor interaction suggests a dynamic, rather than, fixed cutoff risk value for any of these predictors.
Source: Frontiers in Neurology - November 24, 2022 Category: Neurology Source Type: research

Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease
Stroke is a major cause of death or disability. As imaging-based patient stratification improves acute stroke therapy, dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is of major interest in image brain perfusion. However, expert-level perfusion maps require a manual or semi-manual post-processing by a medical expert making the procedure time-consuming and less-standardized. Modern machine learning methods such as generative adversarial networks (GANs) have the potential to automate the perfusion map generation on an expert level without manual validation. We propose a modified pix2pix GAN with a tempo...
Source: Frontiers in Neurology - January 10, 2023 Category: Neurology Source Type: research

Hands-Free Human-Computer Interface Based on Facial Myoelectric Pattern Recognition
Conclusion A facial movement-machine interface was developed in this study in order to help users with limited hand function manipulate electronic devices. Facial movements were detected using four EMG sensors, and five movement patterns were classified using myoelectric pattern recognition algorithms. The results from 10 able-bodied subjects show that facial movements can be detected and classified at high accuracies. The pattern-based continuous mapping between facial movements and cursor actions achieved high performance in both a typing task and a drawing task. Ethics Statement This study was approved by the Committ...
Source: Frontiers in Neurology - April 29, 2019 Category: Neurology Source Type: research

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