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Specialty: Neurology
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Total 1309 results found since Jan 2013.
Design and implementation of a Stroke Rehabilitation Registry for the systematic assessment of processes and outcomes and the development of data-driven prediction models: The STRATEGY study protocol
ConclusionsThis study will test the feasibility of a stroke rehabilitation registry in the Italian health context and provide a systematic assessment of processes and outcomes for quality assessment and benchmarking. By the development of data-driven prediction models in stroke rehabilitation, this study will pave the way for the development of decision support tools for patient-oriented therapy planning and rehabilitation outcomes maximization.Clinical tial registrationThe registration on ClinicalTrials.gov is ongoing and under review. The identification number will be provided when the review process will be completed.
Source: Frontiers in Neurology - October 10, 2022 Category: Neurology Source Type: research
Head-to-head comparison of commercial artificial intelligence solutions for detection of large vessel occlusion at a comprehensive stroke center
ConclusionBoth tools successfully detected most anterior circulation occlusions. RAPID LVO had higher sensitivity while CINA LVO had higher accuracy and specificity. Interestingly, both tools were able to detect some, but not all M2 MCA occlusions. This is the first study to compare traditional and deep learning LVO tools in the clinical setting.
Source: Frontiers in Neurology - October 10, 2022 Category: Neurology Source Type: research
Cerebral blood flow alterations in migraine patients with and without aura: An arterial spin labeling study
ConclusionIn this study, CBF abnormalities of MwA were identified in multiple brain regions, which might help better understand migraine-stroke connection mechanisms and may guide patient-specific decision-making.
Source: The Journal of Headache and Pain - October 4, 2022 Category: Neurology Source Type: research
Development of a convolutional neural network (CNN) based assessment exercise recommendation system for individuals with chronic stroke: a feasibility study
CONCLUSIONS: This CNN deep-learning model provided time-effective and accurate prediction of clinical assessment results and exercise recommendations. This study provides preliminary evidence to support the use of biomechanical data and AI to assist treatment planning and shorten the decision-making process in rehabilitation.PMID:36189968 | DOI:10.1080/10749357.2022.2127669
Source: Topics in Stroke Rehabilitation - October 3, 2022 Category: Neurology Authors: Jiaqi Li Patrick W H Kwong E K Lua Mathew Y L Chan Anna Choo C J W Donnelly Source Type: research
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
Vagus Nerve Stimulation Promotes Motor Learning in Animal Model: A Potential Method for Post-Stroke Recovery
No abstract available
Source: Neurology Today - September 15, 2022 Category: Neurology Tags: At the Bench Source Type: research
Assessing naming errors using an automated machine learning approach.
Objective: After left hemisphere stroke, 20%–50% of people experience language deficits, including difficulties in naming. Naming errors that are semantically related to the intended target (e.g., producing “violin” for picture HARP) indicate a potential impairment in accessing knowledge of word forms and their meanings. Understanding the cause of naming impairments is crucial to better modeling of language production as well as for tailoring individualized rehabilitation. However, evaluation of naming errors is typically by subjective and laborious dichotomous classification. As a result, these evaluations do not ca...
Source: Neuropsychology - September 15, 2022 Category: Neurology Source Type: research
End-to-end artificial intelligence platform for the management of large vessel occlusions: A preliminary study
In this study, we developed a deep learning pipeline that detects large vessel occlusion (LVO) and predicts functional outcome based on computed tomography angiography (CTA) images to improve the management of the LVO patients.
Source: Journal of Stroke and Cerebrovascular Diseases - September 15, 2022 Category: Neurology Authors: Shujuan Meng, Thi My Linh Tran, Mingzhe Hu, PanPan Wang, Thomas Yi, Zhusi Zhong, Luoyun Wang, Braden Vogt, Zhicheng Jiao, Arko Barman, Ugur Cetintemel, Ken Chang, Dat-Thanh Nguyen, Ferdinand K. Hui, Ian Pan, Bo Xiao, Li Yang, Hao Zhou, Harrison X. Bai Source Type: research
Image level detection of large vessel occlusion on 4D-CTA perfusion data using deep learning in acute stroke
Acute ischemic stroke (AIS) secondary to LVOs represent approximately 30-40% of all stroke cases and are associated with disproportionately higher morbidity and mortality.1, 2 The importance of endovascular thrombectomy (EVT) in patients with acute ischemic stroke (AIS) has been well established in multiple randomized controlled trials for patients in both early and late stroke windows.3-6 A critical aspect of the patient triage is the accurate and timely detection of underlying large vessel occlusion (LVO).
Source: Journal of Stroke and Cerebrovascular Diseases - September 10, 2022 Category: Neurology Authors: Girish Bathla, Dhruba Durjoy, Sarv Priya, Edgar Samaniego, Colin P. Derdeyn Source Type: research
Artificial intelligence for early stroke diagnosis in acute vestibular syndrome
ConclusionAI can accurately diagnose a vestibular stroke by using unprocessed vHIT time series. The quantification of eye- and head movements with the use of machine learning and AI can serve in the future for an automated diagnosis in ED patients with acute dizziness. The application of different neural network architectures can potentially further improve performance and enable direct inference from raw video recordings.
Source: Frontiers in Neurology - September 8, 2022 Category: Neurology Source Type: research
The Woven EndoBridge (WEB) Device for the Treatment of Intracranial Aneurysms: Ten Years of Lessons Learned and Adjustments in Practice from the WorldWideWEB Consortium
This study comprised 671 patients (median age 61.4 years; 71.2% female) with 682 intracranial aneurysms. Over time, we observed an increasing tendency to treat patients presenting with ruptured aneurysms and aneurysms with smaller neck, diameter, and dome widths. Furthermore, we observed a trend towards more off-label use of the WEB for sidewall aneurysms and increased adoption of transradial access for WEB deployment. Moreover, the proportion of patients with adequate WEB o cclusion immediately and at last follow-up was significantly higher in more recent year cohorts, as well as lower rates of compaction and retreatment...
Source: Translational Stroke Research - September 6, 2022 Category: Neurology Source Type: research
Effects of Cerebellar Transcranial Direct Current Stimulation in Patients with Stroke: a Systematic Review
ConclusionsctDCS appears to improve poststroke language and motor dysfunction (particularly gait). However, the evidence for these results was insufficient, and the quality of the relevant studies was low. ctDCS stimulation parameters and individual factors of participants may affect the therapeutic effect of ctDCS. Researchers need to take a more regulated approach in the future to conduct studies with large sample sizes. Overall, ctDCS remains a promising stroke intervention technique that could be used in the future.
Source: The Cerebellum - August 27, 2022 Category: Neurology Source Type: research
