• Filter By:
• Specialty
• Source
• Condition
• Cancer
• Infectious Disease
• Drug
• Training
• Management
• Procedure
• Therapy
• Vaccine
• Nutrition
• Country

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

Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis
ConclusionA fast and fully automatic method can be used for stroke subtype risk assessment and classification based on fundus photographs alone.
Source: Frontiers in Neurology - August 22, 2022 Category: Neurology Source Type: research

Middle School Students Effectively Improve Stroke Knowledge and Pass Them to Family Members in China Using Stroke 1-2-0
Conclusion: Middle school and high school students can effectively use Stroke 1-2-0 to improve their stroke knowledge and pass this knowledge to their family members. Sustained educational efforts and repeated educational events are needed though.
Source: Frontiers in Neurology - April 7, 2020 Category: Neurology Source Type: research

Clustering and prediction of long-term functional recovery patterns in first-time stroke patients
ConclusionsThe longitudinal, multi-dimensional, functional assessment data of first-time stroke patients were successfully clustered, and the prediction models showed relatively good accuracies. Early identification and prediction of long-term functional outcomes will help clinicians develop customized treatment strategies.
Source: Frontiers in Neurology - March 8, 2023 Category: Neurology Source Type: research

Expression of Cytokines and Chemokines as Predictors of Stroke Outcomes in Acute Ischemic Stroke
Conclusions: Machine learning algorithms can be employed to develop prognostic predictive biomarkers for stroke outcomes in ischemic stroke patients, particularly in regard to identifying acute gene expression changes that occur during stroke.
Source: Frontiers in Neurology - January 14, 2020 Category: Neurology Source Type: research

Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms
Conclusions: DAMS and R-DAMS, as prediction-driven decision support tools, were designed to aid clinical decision-making for mild stroke patients in emergency contexts. In addition, even within a narrow range of baseline scores, NIHSS on admission is the strongest feature that contributed to the prediction.
Source: Frontiers in Neurology - December 23, 2021 Category: Neurology Source Type: research

Exploring How Low Oxygen Post Conditioning Improves Stroke-Induced Cognitive Impairment: A Consideration of Amyloid-Beta Loading and Other Mechanisms
Cognitive impairment is a common and disruptive outcome for stroke survivors, which is recognized to be notoriously difficult to treat. Previously, we have shown that low oxygen post-conditioning (LOPC) improves motor function and limits secondary neuronal loss in the thalamus after experimental stroke. There is also emerging evidence that LOPC may improve cognitive function post-stroke. In the current study we aimed to explore how exposure to LOPC may improve cognition post-stroke. Experimental stroke was induced using photothrombotic occlusion in adult, male C57BL/6 mice. At 72 h post-stroke animals were randomly assigne...
Source: Frontiers in Neurology - March 24, 2021 Category: Neurology Source Type: research

Application of Machine Learning Techniques to Identify Data Reliability and Factors Affecting Outcome After Stroke Using Electronic Administrative Records
Conclusion: Electronic administrative records from this cohort produced reliable outcome prediction and identified clinically appropriate factors negatively impacting most outcome variables following hospital admission with stroke. This presents a means of future identification of modifiable factors associated with patient discharge destination. This may potentially aid in patient selection for certain interventions and aid in better patient and clinician education regarding expected discharge outcomes.
Source: Frontiers in Neurology - September 27, 2021 Category: Neurology Source Type: research

Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke
ConclusionThis is the first study to address BP management in the acute phase of ischemic stroke using ML techniques. The results indicate that the treatment choice should be adjusted to different clinical and BP parameters, thus, providing a better decision-making approach.
Source: Frontiers in Neurology - February 14, 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

Predictors of Function, Activity, and Participation of Stroke Patients Undergoing Intensive Rehabilitation: A Multicenter Prospective Observational Study Protocol
Discussion: By identifying data-driven prognosis prediction models in stroke rehabilitation, this study might contribute to the development of patient-oriented therapy and to optimize rehabilitation outcomes.Clinical Trial Registration:ClinicalTrials.gov, NCT03968627. https://www.clinicaltrials.gov/ct2/show/NCT03968627?term=Cecchi&cond=Stroke&draw=2&rank=2.
Source: Frontiers in Neurology - April 8, 2021 Category: Neurology Source Type: research

Identification of a miRNA –mRNA regulatory network for post-stroke depression: a machine-learning approach
ConclusionThe study highlighted gene signatures for PSD with three genes (SPATA2, ZNF208, and YTHDC1) and four upstream miRNAs (miR-6883-5p, miR-6873-3p, miR-4776-3p, and miR-6738-3p). These biomarkers could further our understanding of the pathogenesis of PSD.
Source: Frontiers in Neurology - July 17, 2023 Category: Neurology Source Type: research

Using Transcranial Direct Current Stimulation to Augment the Effect of Motor Imagery-Assisted Brain-Computer Interface Training in Chronic Stroke Patients —Cortical Reorganization Considerations
Conclusion: MI-BCI improved the motor function of the stroke-affected arm in chronic stroke patients with moderate to severe impairment. tDCS did not confer overall additional benefit although there was a trend toward greater benefit. Cortical activity changes in the contralesional M1 associated with functional improvement suggests a possible role for the contralesional M1 in stroke recovery in more severely affected patients. This has important implications in designing neuromodulatory interventions for future studies and tailoring treatment.Clinical Trial Registration: The study was registered at https://clinicaltrials.gov (NCT01897025).
Source: Frontiers in Neurology - August 26, 2020 Category: Neurology Source Type: research

Machine Learning-Enabled 30-Day Readmission Model for Stroke Patients
Conclusions: Machine learning-based models can be designed to predict 30-day readmission after stroke using structured data from EHR. Among the algorithms analyzed, XGBoost with ROSE-sampling had the best performance in terms of AUC while LR with ROSE-sampling and feature selection had the best sensitivity. Clinical variables highly associated with 30-day readmission could be targeted for personalized interventions. Depending on healthcare systems' resources and criteria, models with optimized performance metrics can be implemented to improve outcomes.
Source: Frontiers in Neurology - March 31, 2021 Category: Neurology Source Type: research

Assessment Methods of Post-stroke Gait: A Scoping Review of Technology-Driven Approaches to Gait Characterization and Analysis
This study aimed to review and summarize research efforts applicable to quantification and analyses of post-stroke gait with focus on recent technology-driven gait characterization and analysis approaches, including the integration of smart low cost wearables and Artificial Intelligence (AI), as well as feasibility and potential value in clinical settings.Methods: A comprehensive literature search was conducted within Google Scholar, PubMed, and ScienceDirect using a set of keywords, including lower extremity, walking, post-stroke, and kinematics. Original articles that met the selection criteria were included.Results and ...
Source: Frontiers in Neurology - June 8, 2021 Category: Neurology Source Type: research

Pages: 1  2  3  4  5  6  7