AIMC Topic: Stroke
Clear Filters Showing 661 to 670 of 1164 articles
Stroke Prediction with Machine Learning Methods among Older Chinese.
International journal of environmental research and public health
Mar 12, 2020
Timely stroke diagnosis and intervention are necessary considering its high prevalence. Previous studies have mainly focused on stroke prediction with balanced data. Thus, this study aimed to develop machine learning models for predicting stroke with...
Impact of initial flexor synergy pattern scores on improving upper extremity function in stroke patients treated with adjunct robotic rehabilitation: A randomized clinical trial.
Topics in stroke rehabilitation
Mar 10, 2020
Robot-assisted rehabilitation is an appealing strategy for patients after stroke, as it generates repetitive movements in a consistent, precise, and automated manner. To identify patients who will benefit most from robotic rehabilitation for upper ...
Robot-assisted therapy for arm recovery for stroke patients: state of the art and clinical implication.
Expert review of medical devices
Feb 28, 2020
: Robot-assisted therapy is an emerging approach that performs highly repetitive, intensive, task oriented and quantifiable neuro-rehabilitation. In the last decades, it has been increasingly used in a wide range of neurological central nervous syste...
A randomized controlled study incorporating an electromechanical gait machine, the Hybrid Assistive Limb, in gait training of patients with severe limitations in walking in the subacute phase after stroke.
PloS one
Feb 28, 2020
Early onset, intensive and repetitive, gait training may improve outcome after stroke but for patients with severe limitations in walking, rehabilitation is a challenge. The Hybrid Assistive Limb (HAL) is a gait machine that captures voluntary action...
Letter to the Editor Re: "The Effects of a Robot-Assisted Arm Training Plus Hand Functional Electrical Stimulation on Recovery After Stroke: A Randomized Clinical Trial".
Archives of physical medicine and rehabilitation
Feb 7, 2020
Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry.
Computer methods and programs in biomedicine
Feb 1, 2020
INTRODUCTION: Being able to predict functional outcomes after a stroke is highly desirable for clinicians. This allows clinicians to set reasonable goals with patients and relatives, and to reach shared after-care decisions for recovery or rehabilita...
Machine Learning for Detecting Early Infarction in Acute Stroke with Non-Contrast-enhanced CT.
Radiology
Jan 28, 2020
Background Identifying the presence and extent of infarcted brain tissue at baseline plays a crucial role in the treatment of patients with acute ischemic stroke (AIS). Patients with extensive infarction are unlikely to benefit from thrombolysis or t...
Machine Learning Approach to Identify Stroke Within 4.5 Hours.
Stroke
Jan 28, 2020
Background and Purpose- We aimed to investigate the ability of machine learning (ML) techniques analyzing diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging to identify patients within the reco...
The Role of Robotic Path Assistance and Weight Support in Facilitating 3D Movements in Individuals With Poststroke Hemiparesis.
Neurorehabilitation and neural repair
Jan 20, 2020
. High-intensity repetitive training is challenging to provide poststroke. Robotic approaches can facilitate such training by unweighting the limb and/or by improving trajectory control, but the extent to which these types of assistance are necessary...
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