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Specialty: Neurology
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Total 1309 results found since Jan 2013.
Stroke mortality prediction using machine learning: systematic review
Accurate prognostication of stroke may help in appropriate therapy and rehabilitation planning. In the past few years, several machine learning (ML) algorithms were applied for prediction of stroke outcomes. We aimed to examine the performance of machine learning –based models for the prediction of mortality after stroke, as well as to identify the most prominent factors for mortality.
Source: Journal of the Neurological Sciences - December 20, 2022 Category: Neurology Authors: Lihi Schwartz, Roi Anteby, Eyal Klang, Shelly Soffer Tags: Review Article Source Type: research
Stroke mortality prediction using machine learning: A systematic review
Accurate prognostication of stroke may help in appropriate therapy and rehabilitation planning. In the past few years, several machine learning (ML) algorithms were applied for prediction of stroke outcomes. We aimed to examine the performance of machine learning –based models for the prediction of mortality after stroke, as well as to identify the most prominent factors for mortality.
Source: Journal of the Neurological Sciences - December 20, 2022 Category: Neurology Authors: Lihi Schwartz, Roi Anteby, Eyal Klang, Shelly Soffer Tags: Review Article Source Type: research
School of Thrombectomy —A 3-Step Approach to Perform Acute Stroke Treatment with Simulator Training and Virtual Supervision by Remote Streaming Support (RESS)
AbstractAs the number of neurointerventional procedures continues to increase, so does the need for well-trained neurointerventionalists. The purpose of this work was to establish and assess a systematic 3‑step approach to perform acute stroke treatment including simulator training and virtual supervision by remote streaming support (RESS). Five trainees (four men, one women) who have completed the 3‑step approach have answered an 11-item questionnaire (5-point Likert scale) in orde r to evaluate training step 1 (simulator). Furthermore, all trainees and one supervisor (female) answered a standardized questionnaire...
Source: Clinical Neuroradiology - December 15, 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
A phase II randomised controlled trial evaluating the feasibility and preliminary efficacy of an education program on speech-language pathologist' self-efficacy, and self-rated competency for counselling to support psychological wellbeing in people with post-stroke aphasia
CONCLUSIONS: The demonstrated feasibility and preliminary efficacy of this online counseling program warrant a future definitive trial.PMID:36440678 | DOI:10.1080/10749357.2022.2145736
Source: Topics in Stroke Rehabilitation - November 28, 2022 Category: Neurology Authors: Jasvinder K Sekhon Jennifer Oates Ian Kneebone Miranda L Rose Source Type: research
Memory decline in young stroke survivors during a 9-year follow-up: A cohort study
ConclusionYoung stroke survivors might be at risk of memory decline over the decade following the stroke.
Source: Frontiers in Neurology - November 25, 2022 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
The White Matter Functional Abnormalities in Patients with Transient Ischemic Attack: A Reinforcement Learning Approach
CONCLUSION: The present study revealed abnormal WM functional alterations in the low-frequency range in patients with TIA. These results support the role of WM functional neural activity as a potential neuromarker in classifying patients with TIA and offer novel insights into the underlying mechanisms in patients with TIA from the perspective of WM function.PMID:36300173 | PMC:PMC9592236 | DOI:10.1155/2022/1478048
Source: Neural Plasticity - October 27, 2022 Category: Neurology Authors: Huibin Ma Zhou Xie Lina Huang Yanyan Gao Linlin Zhan Su Hu Jiaxi Zhang Qingguo Ding Source Type: research
The Relationship between Altered Degree Centrality and Cognitive Function in Mild Subcortical Stroke: A Resting-State fMRI Study
CONCLUSIONS: DC values were increased in the right PhG following a mild subcortical stroke. DC values in the PhG were negatively correlated with cognitive function, which may indicate brain nodes reorganization.PMID:36265670 | DOI:10.1016/j.brainres.2022.148125
Source: Brain Research - October 20, 2022 Category: Neurology Authors: Yan Min Chang Liu Lijun Zuo Yongjun Wang Zixiao Li Source Type: research
The feasibility and accuracy of machine learning in improving safety and efficiency of thrombolysis for patients with stroke: Literature review and proposed improvements
In this study, we identified 29 related previous machine learning models, reviewed the models on the accuracy and feasibility, and proposed corresponding improvements. Regarding accuracy, lack of long-term outcome, treatment option consideration, and advanced radiological features were found in many previous studies in terms of model conceptualization. Regarding interpretability, most of the previous models chose restrictive models for high interpretability and did not mention processing time consideration. In the future, model conceptualization could be improved based on comprehensive neurological domain knowledge and fea...
Source: Frontiers in Neurology - October 20, 2022 Category: Neurology Source Type: research
The mucormycosis and Stroke: the learning curve during the second COVID-19 pandemic
Background The Angio-invasive Rhino-orbito-cerebral mucormycosis (ROCM) producing strokes is a less explored entity. Our hospital, a stroke-ready one, had an opportunity to manage mucormycosis when it was identified as the nodal center for mucormycosis management. We are sharing our experiences and mistakes in managing the cerebrovascular manifestations of ROCM.Methods We conducted a prospective observational study during the second wave of the COVID-19 pandemic from 1st May 2021 to 30th September 2021, where consecutive patients aged more than 18 years with microbiologically confirmed cases of ROCM were included.
Source: Journal of Stroke and Cerebrovascular Diseases - October 12, 2022 Category: Neurology Authors: Dileep Ramachandran, Aravind R, Praveen Panicker, Jayaprabha S, MC Sathyabhama, Abhilash Nair, Raj S. Chandran, Simon George, Chintha S, Thomas Iype Source Type: research
