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Specialty: Neurology
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Total 1309 results found since Jan 2013.

A Unique Signature of Cardiac-Induced Cranial Forces During Acute Large Vessel Stroke and Development of a Predictive Model
ConclusionsHeadpulse recordings performed on patients with suspected acute stroke significantly identify those with LVO. The lack of temporal correlation of the headpulse with cardiac contraction and resolution to normal may reflect changes in cerebral blood flow and may provide a useful technique to triage stroke patients for thrombectomy using a noninvasive device.
Source: Neurocritical Care - October 6, 2019 Category: Neurology Source Type: research

Alternative Motor Task-Based Pattern Training With a Digital Mirror Therapy System Enhances Sensorimotor Signal Rhythms Post-stroke
Mirror therapy (MT) facilitates motor learning and induces cortical reorganization and motor recovery from stroke. We applied the new digital mirror therapy (DMT) system to compare the cortical activation under the three visual feedback conditions: (1) no mirror visual feedback (NoMVF), (2) bilateral synchronized task-based mirror visual feedback training (BMVF), and (3) reciprocal task-based mirror visual feedback training (RMVF). During DMT, EEG recordings, including time-dependent event-related desynchronization (ERD) signal amplitude in both mu and beta bands, were obtained from the standard C3 (ispilesional hemisphere...
Source: Frontiers in Neurology - November 21, 2019 Category: Neurology Source Type: research

Surgical Approaches to Stroke Risk Reduction
This article examines the evidence for using the available options. RECENT FINDINGS Carotid endarterectomy is an effective treatment option for reducing the risk of stroke in appropriately selected patients. Patients should be stratified for future stroke risk based on both the degree of stenosis and the presence of symptoms referable to the culprit lesion. Carotid stenting is also useful in reducing stroke risk, again in carefully selected patients. Because of the publication of significant data regarding both carotid endarterectomy and carotid artery stenting in the last several years, selection can be far more person...
Source: CONTINUUM: Lifelong Learning in Neurology - April 1, 2020 Category: Neurology Tags: REVIEW ARTICLES Source Type: research

Treatment Effects of Upper Limb Action Observation Therapy and Mirror Therapy on Rehabilitation Outcomes after Subacute Stroke: A Pilot Study.
Conclusion: The preliminary results found that the patients in the action observation therapy and active control intervention groups had comparable benefits, suggesting that the 2 treatments might be used as an alternative to each other. A further large-scale study with at least 20 patients in each group to validate the study findings is needed. This trial is registered with NCT02871700. PMID: 32377266 [PubMed - in process]
Source: Behavioural Neurology - May 8, 2020 Category: Neurology Authors: Hsieh YW, Lin YH, Zhu JD, Wu CY, Lin YP, Chen CC Tags: Behav Neurol Source Type: research

Prediction of Progression to Severe Stroke in Initially Diagnosed Anterior Circulation Ischemic Cerebral Infarction
Conclusion: The U-Net was fully automatic and showed a high correlation with manual segmentation. An integrated approach combining clinical variables and stroke lesion volumes that were derived from the advanced machine learning algorithms had high accuracy in predicting the progression to severe stroke in ASACNLII patients.
Source: Frontiers in Neurology - June 18, 2021 Category: Neurology Source Type: research

Accelerating Prediction of Malignant Cerebral Edema After Ischemic Stroke with Automated Image Analysis and Explainable Neural Networks
ConclusionsAn LSTM neural network incorporating volumetric data extracted from routine CT scans identified all cases of malignant cerebral edema by 24  h after stroke, with significantly fewer false positives than a fully connected neural network, regression model, and the validated EDEMA score. This preliminary work requires prospective validation but provides proof of principle that a deep learning framework could assist in selecting patients f or surgery prior to deterioration.
Source: Neurocritical Care - August 20, 2021 Category: Neurology Source Type: research

Spatial Neglect and Anosognosia After Right Brain Stroke
This article guides neurologists’ assessment of right brain cognitive disorders and describes how to efficiently assemble and direct a treatment team to address spatial neglect and unawareness of deficit.
Source: CONTINUUM: Lifelong Learning in Neurology - December 1, 2021 Category: Neurology Tags: REVIEW ARTICLES 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

Deep Convolution Generative Adversarial Network-Based Electroencephalogram Data Augmentation for Post-Stroke Rehabilitation with Motor Imagery
Int J Neural Syst. 2022 Jul 25:2250039. doi: 10.1142/S0129065722500393. Online ahead of print.ABSTRACTThe motor imagery brain-computer interface (MI-BCI) system is currently one of the most advanced rehabilitation technologies, and it can be used to restore the motor function of stroke patients. The deep learning algorithms in the MI-BCI system require lots of training samples, but the electroencephalogram (EEG) data of stroke patients is quite scarce. Therefore, the expansion of EEG data has become an important part of stroke clinical rehabilitation research. In this paper, a deep convolution generative adversarial networ...
Source: International Journal of Neural Systems - July 26, 2022 Category: Neurology Authors: Fangzhou Xu Gege Dong Jincheng Li Qingbo Yang Lei Wang Yanna Zhao Yihao Yan Jinzhao Zhao Shaopeng Pang Dongju Guo Yang Zhang Jiancai Leng Source Type: research

Analyzing and predicting the risk of death in stroke patients using machine learning
ConclusionWe used several highly interpretive machine learning models to predict stroke prognosis with the highest accuracy to date and to identify heterogeneous treatment effects of warfarin and human albumin in stroke patients. Our interpretation of the model yielded a number of findings that are consistent with clinical knowledge and warrant further study and verification.
Source: Frontiers in Neurology - February 3, 2023 Category: Neurology Source Type: research

Machine learning in the prediction of post-stroke cognitive impairment: a systematic review and meta-analysis
ConclusionML is a potential tool for predicting PSCI and may be used to develop simple clinical scoring scales for subsequent clinical use.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=383476.
Source: Frontiers in Neurology - August 3, 2023 Category: Neurology Source Type: research