AIMC Topic: Stroke

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Using machine learning models to improve stroke risk level classification methods of China national stroke screening.

BMC medical informatics and decision making Dec 10, 2019
BACKGROUND: With the character of high incidence, high prevalence and high mortality, stroke has brought a heavy burden to families and society in China. In 2009, the Ministry of Health of China launched the China national stroke screening and interv...
Mass Screening Decision Trees Stroke Algorithms Decision Support Techniques Adult Incidence Logistic Models Risk Assessment China Humans Neural Networks, Computer Machine Learning
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A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images.

NeuroImage. Clinical Dec 9, 2019
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would also greatly facilitate the study of brain-behavior relationships by...
Humans Neural Networks, Computer Brain Imaging, Three-Dimensional Neuroimaging Magnetic Resonance Imaging Stroke Image Interpretation, Computer-Assisted
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Orbit image analysis machine learning software can be used for the histological quantification of acute ischemic stroke blood clots.

PloS one Dec 5, 2019
Our aim was to assess the utility of a novel machine learning software (Orbit Image Analysis) in the histological quantification of acute ischemic stroke (AIS) clots. We analyzed 50 AIS blood clots retrieved using mechanical thrombectomy procedures. ...
Erythrocytes Young Adult Adult Machine Learning Male Humans Stroke Female Software Middle Aged Brain Ischemia Thrombosis Aged Cohort Studies Aged, 80 and over Artifacts Image Processing, Computer-Assisted Orbit
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Potential of machine learning methods to identify patients with nonvalvular atrial fibrillation.

Future cardiology Dec 3, 2019
Nonvalvular atrial fibrillation (NVAF) is associated with an increased risk of stroke however many patients are diagnosed after onset. This study assessed the potential of machine-learning algorithms to detect NVAF. A retrospective database study u...
Humans Machine Learning Algorithms Retrospective Studies Male Follow-Up Studies Stroke Atrial Fibrillation Female Risk Factors Aged
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Effectiveness of Intervention Based on End-effector Gait Trainer in Older Patients With Stroke: A Systematic Review.

Journal of the American Medical Directors Association Nov 29, 2019
OBJECTIVE: The objective of the article is to analyze the effects of the end-effector technology for gait rehabilitation on acute, subacute, and chronic stroke in order to verify the efficacy of the treatment in older people, based on evidence from r...
Humans Aged Aged, 80 and over Walking Stroke Rehabilitation Robotics Gait Gait Disorders, Neurologic Stroke
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[Predicting atrial fibrillation through a sinus-rhythm electrocardiogram; useful or not?].

Nederlands tijdschrift voor geneeskunde Nov 28, 2019
In patients with cryptogenic stroke, the detection of atrial fibrillation (AF) is important, since it is an indication for the prescription of oral anticoagulation, instead of anti-platelet therapy, to decrease the chance of a recurrent ischaemic cer...
Predictive Value of Tests Decision Support Techniques Anticoagulants Humans Reproducibility of Results Atrial Fibrillation Stroke Artificial Intelligence Electrocardiography Algorithms
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The neural and neurocomputational bases of recovery from post-stroke aphasia.

Nature reviews. Neurology Nov 26, 2019
Language impairment, or aphasia, is a disabling symptom that affects at least one third of individuals after stroke. Some affected individuals will spontaneously recover partial language function. However, despite a growing number of investigations, ...
Humans Neural Networks, Computer Brain Aphasia Recovery of Function Stroke
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Data-driven analyses of motor impairments in animal models of neurological disorders.

PLoS biology Nov 21, 2019
Behavior provides important insights into neuronal processes. For example, analysis of reaching movements can give a reliable indication of the degree of impairment in neurological disorders such as stroke, Parkinson disease, or Huntington disease. T...
Nervous System Diseases Motor Skills Movement Forelimb Motor Activity Motor Disorders Rats Disease Models, Animal Stroke Animals Male Image Processing, Computer-Assisted Neural Networks, Computer
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Platelet-rich emboli are associated with von Willebrand factor levels and have poorer revascularization outcomes.

Journal of neurointerventional surgery Nov 4, 2019
BACKGROUND AND AIMS: Platelets and von Willebrand factor (vWF) are key factors in thrombosis and thus are likely key components of acute ischemic stroke (AIS) emboli. We aimed to characterize platelet and vWF levels in AIS emboli and to assess associ...
Treatment Outcome Stroke Brain Ischemia Blood Platelets Machine Learning Female Male von Willebrand Factor Thromboembolism Cerebral Revascularization Humans
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Machine Learning-Based Forecast of Hemorrhagic Stroke Healthcare Service Demand considering Air Pollution.

Journal of healthcare engineering Nov 3, 2019
This study aimed to forecast the pattern of the demand for hemorrhagic stroke healthcare services based on air quality and machine learning. Hemorrhagic stroke, air quality, and meteorological data for 2016-2017 were obtained from the Longquanyi Dist...
Models, Statistical Air Pollution Stroke Seasons Health Services Needs and Demand Forecasting Humans Databases, Factual Hospitalization Machine Learning China
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