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The Pragmatic Classification of Upper Extremity Motion in Neurological Patients: A Primer
Recent advances in wearable sensor technology and machine learning (ML) have allowed for the seamless and objective study of human motion in clinical applications, including Parkinson's disease, and stroke. Using ML to identify salient patterns in sensor data has the potential for widespread application in neurological disorders, so understanding how to develop this approach for one's area of inquiry is vital. We previously proposed an approach that combined wearable inertial measurement units (IMUs) and ML to classify motions made by stroke patients. However, our approach had computational and practical limitations. We ad...
Source: Frontiers in Neurology - September 17, 2019 Category: Neurology Source Type: research

Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy
ConclusionOur study firstly demonstrated that the LR-model with 9 common variables has the best-performance to predict the risk of post-stroke SCD due to CC infarcton. Particularly, the combination of LR-model and SHAP-explainer could aid in achieving personalized risk prediction and be served as a decision-making tool for early intervention since its poor long-term outcome.
Source: Frontiers in Neurology - June 9, 2023 Category: Neurology Source Type: research

More Research Is Needed on Lifestyle Behaviors That Influence Progression of Parkinson's Disease
This article highlights some of these challenges in the design of lifestyle studies in PD, and suggests a more coordinated international effort is required, including ongoing longitudinal observational studies. In combination with pharmaceutical treatments, healthy lifestyle behaviors may slow the progression of PD, empower patients, and reduce disease burden. For optimal care of people with PD, it is important to close this gap in current knowledge and discover whether such associations exist. Introduction Parkinson's disease (PD) is an age-related complex progressive neurodegenerative disorder, with key p...
Source: Frontiers in Neurology - April 29, 2019 Category: Neurology Source Type: research

Influence of the Intensive Care Unit Environment on the Reliability of the Montreal Cognitive Assessment
Conclusions: The reliability of the MoCA was excellent, independent from the testing environment being ICU or office. This finding is helpful for patient care and studies investigating the effect of therapeutic interventions on the neuropsychological outcome after SAH, stroke or traumatic brain injury.
Source: Frontiers in Neurology - July 2, 2019 Category: Neurology Source Type: research

Intra-arterial Administration of Human Umbilical Cord Blood Derived Cells Inversed Learning Asymmetry Resulting From Focal Brain Injury in Rat
Conclusions: Intraarterial infusion of HUCB-derived cells inversed lateralized performance of learning task resulting from focal brain damage. The inversion was not visible in any other of the used motor as well as cognitive tests. The observed behavioral effect of cell infusion was also not related to the range of the brain damage. Our findings contribute to describing the effects of systemic treatment with the HUCB-derived cells on functional recovery following focal brain injury.
Source: Frontiers in Neurology - August 12, 2019 Category: Neurology Source Type: research

Behavioral Assessment of Sensory, Motor, Emotion, and Cognition in Rodent Models of Intracerebral Hemorrhage
Intracerebral hemorrhage (ICH) is the second most common type of stroke and has one of the highest fatality rates of any disease. There are many clinical signs and symptoms after ICH due to brain cell injury and network disruption resulted from the rupture of a tiny artery and activation of inflammatory cells, such as motor dysfunction, sensory impairment, cognitive impairment, and emotional disturbance, etc. Thus, researchers have established many tests to evaluate behavioral changes in rodent ICH models, in order to achieve a better understanding and thus improvements in the prognosis for the clinical treatment of stroke...
Source: Frontiers in Neurology - June 17, 2021 Category: Neurology Source Type: research

Machine learning to predict futile recanalization of large vessel occlusion before and after endovascular thrombectomy
ConclusionsThe “Early” XGBoost and the “Late” XGBoost allowed us to predict futile recanalization before and after EVT accurately. Our study suggests that including peri-interventional characteristics may lead to superior predictive performance compared to a model based on baseline characteristics only. In addition, NIHSS after 24 h was the most important prognostic factor for futile recanalization.
Source: Frontiers in Neurology - August 19, 2022 Category: Neurology Source Type: research

Rehabilomics: A state-of-the-art review of framework, application, and future considerations
Rehabilomics is an important research framework that allows omics research built upon rehabilitation practice, especially in function evaluation, outcome prediction, and individualized rehabilitation. In the field of rehabilomics, biomarkers can serve as objectively measured indicators for body functioning, so as to complement the International Classification of Functioning, Disability, and Health (ICF) assessment. Studies on traumatic brain injury (TBI), stroke, and Parkinson's disease have shown that biomarkers (such as serum markers, MRI, and digital signals derived from sensors) are correlated with diagnosis, disease s...
Source: Frontiers in Neurology - March 8, 2023 Category: Neurology Source Type: research

Application of Machine Learning to Automated Analysis of Cerebral Edema in Large Cohorts of Ischemic Stroke Patients
Rajat Dhar, Yasheng Chen, Hongyu An, Jin-Moo Lee
Source: Frontiers in Neurology - August 21, 2018 Category: Neurology Source Type: research

Machine Learning in Acute Ischemic Stroke Neuroimaging
Haris Kamal, Victor Lopez, Sunil A. Sheth
Source: Frontiers in Neurology - November 8, 2018 Category: Neurology Source Type: research

Learning to Predict Ischemic Stroke Growth on Acute CT Perfusion Data by Interpolating Low-Dimensional Shape Representations
Christian Lucas, Andr é Kemmling, Nassim Bouteldja, Linda F. Aulmann, Amir Madany Mamlouk, Mattias P. Heinrich
Source: Frontiers in Neurology - November 26, 2018 Category: Neurology Source Type: research

Light-Induced Pupillary Responses in Alzheimer's Disease
Light-Induced Pupillary Responses in Alzheimer's Disease Pratik S. Chougule1, Raymond P. Najjar1,2, Maxwell T. Finkelstein1, Nagaendran Kandiah3,4 and Dan Milea1,2,5* 1Department of Visual Neurosciences, Singapore Eye Research Institute, Singapore, Singapore 2The Ophthalmology & Visual Sciences ACP, Duke-National University of Singapore (NUS) Medical School, Singapore, Singapore 3Department of Neurology, National Neuroscience Institute, Singapore, Singapore 4Duke-National University of Singapore (NUS), Singapore, Singapore 5Singapore National Eye Centre, Singapore, Singapore The impact of Alzhe...
Source: Frontiers in Neurology - April 11, 2019 Category: Neurology Source Type: research

Beta Amyloid Deposition Is Not Associated With Cognitive Impairment in Parkinson's Disease
In this study, we used a well-validated visual assessment to clinically rate scans as being amyloid positive or negative (38). As there is not an accepted threshold based on standardized centiloid reference regions, we defined an amyloid positivity centiloid cut-off threshold in our sample. Our cut-off (CL = 31.3, SUVR = 1.21) corresponds well to the estimated value proposed by Rowe and colleagues (34) in the context of AD (CL = 25–30), however our estimated threshold may be biased by the low number of Aβ positive patients. Our results suggest a lower prevalence of amyloid-positive PDD individuals than in ...
Source: Frontiers in Neurology - April 23, 2019 Category: Neurology Source Type: research

The Predictive Capacity of the Buffalo Concussion Treadmill Test After Sport-Related Concussion in Adolescents
Conclusion This study found that the ΔHR (HRt minus resting HR) correlated with duration of clinical recovery in participants who were prescribed relative rest or a placebo-stretching program but not for participants prescribed sub-threshold aerobic exercise. A ΔHR of ≤50 bpm on the BCTT was 73% sensitive and 78% specific for predicting delayed recovery in concussed adolescents prescribed the current standard of care (i.e., cognitive and physical rest). This has implications for planning team and school activities in adolescents who sustain SRC. Ethics Statement This study was carried out in acco...
Source: Frontiers in Neurology - April 23, 2019 Category: Neurology Source Type: research

Editorial: Machine Learning and Decision Support in Stroke
Source: Frontiers in Neurology - May 28, 2020 Category: Neurology Source Type: research

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