AIMC Topic: Stroke
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Artificial Intelligence Applications in Stroke.
Stroke
Jul 22, 2020
Integrating uncertainty in deep neural networks for MRI based stroke analysis.
Medical image analysis
Jul 19, 2020
At present, the majority of the proposed Deep Learning (DL) methods provide point predictions without quantifying the model's uncertainty. However, a quantification of the reliability of automated image analysis is essential, in particular in medicin...
Robotic assessment of rapid motor decision making in children with perinatal stroke.
Journal of neuroengineering and rehabilitation
Jul 14, 2020
BACKGROUND: Activities of daily living frequently require children to make rapid decisions and execute desired motor actions while inhibiting unwanted actions. Children with hemiparetic cerebral palsy due to perinatal stroke may have deficits in exec...
Identifying diagnosis evidence of cardiogenic stroke from Chinese echocardiograph reports.
BMC medical informatics and decision making
Jul 9, 2020
BACKGROUND: Cardiogenic stroke has increasing morbidity in China and brought economic burden to patient families. In cardiogenic stroke diagnosis, echocardiograph examination is one of the most important examinations. Sonographers will investigate pa...
Systematic review with network meta-analysis of randomized controlled trials of robotic-assisted arm training for improving activities of daily living and upper limb function after stroke.
Journal of neuroengineering and rehabilitation
Jun 30, 2020
BACKGROUND: The aim of the present study was to to assess the relative effectiveness of the various types of electromechanical-assisted arm devices and approaches after stroke.
Robot-assisted therapy for upper-limb rehabilitation in subacute stroke patients: A systematic review and meta-analysis.
Brain and behavior
Jun 26, 2020
BACKGROUND: Stroke survivors often experience upper-limb motor deficits and achieve limited motor recovery within six months after the onset of stroke. We aimed to systematically review the effects of robot-assisted therapy (RT) in comparison to usua...
A machine learning approach to select features important to stroke prognosis.
Computational biology and chemistry
Jun 23, 2020
Ischemic stroke is a common neurological disorder, and is still the principal cause of serious long-term disability in the world. Selection of features related to stroke prognosis is highly valuable for effective intervention and treatment. In this s...
Machine learning and natural language processing methods to identify ischemic stroke, acuity and location from radiology reports.
PloS one
Jun 19, 2020
Accurate, automated extraction of clinical stroke information from unstructured text has several important applications. ICD-9/10 codes can misclassify ischemic stroke events and do not distinguish acuity or location. Expeditious, accurate data extra...
The ReWalk ReStore™ soft robotic exosuit: a multi-site clinical trial of the safety, reliability, and feasibility of exosuit-augmented post-stroke gait rehabilitation.
Journal of neuroengineering and rehabilitation
Jun 18, 2020
BACKGROUND: Atypical walking in the months and years after stroke constrain community reintegration and reduce mobility, health, and quality of life. The ReWalk ReStore™ is a soft robotic exosuit designed to assist the propulsion and ground clearance...
Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors.
Indian heart journal
Jun 18, 2020
MOTIVATION: Machine learning (ML)-based stroke risk stratification systems have typically focused on conventional risk factors (CRF) (AtheroRisk-conventional). Besides CRF, carotid ultrasound image phenotypes (CUSIP) have shown to be powerful phenoty...
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