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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

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

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

Leveraging Factors of Self-Efficacy and Motivation to Optimize Stroke Recovery
The International Classification of Functioning, Disability and Health framework recognizes that an individual's functioning post-stroke reflects an interaction between their health condition and contextual factors encompassing personal and environmental factors. Personal factors significantly impact rehabilitation outcomes as they determine how an individual evaluates their situation and copes with their condition in daily life. A key personal factor is self-efficacy—an individual's belief in their capacity to achieve certain outcomes. Self-efficacy influences an individual's motivational state to execute behaviors nece...
Source: Frontiers in Neurology - February 24, 2022 Category: Neurology Source Type: research

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

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

Predicting Poor Outcome Before Endovascular Treatment in Patients With Acute Ischemic Stroke
Conclusions: All prediction models showed a high AUC. The best-performing models correctly identified 34% of the poor outcome patients at a cost of misclassifying 4% of non-poor outcome patients. Further studies are necessary to determine whether these accuracies are reproducible before implementation in clinical practice.
Source: Frontiers in Neurology - October 15, 2020 Category: Neurology Source Type: research

Comparing Poor and Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy in Acute Ischemic Stroke
ConclusionsOur results suggest that a prediction of poor outcome after AIS and MT could be made based on clinical baseline variables only. Speed and extent of MT did improve prediction for a favorable outcome but is not relevant for poor outcome. An MR mismatch with small ischemic core and larger penumbral tissue showed no predictive importance.
Source: Frontiers in Neurology - May 27, 2022 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

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

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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