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Stroke

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Computed Tomography Images under Artificial Intelligence Algorithms on the Treatment Evaluation of Intracerebral Hemorrhage with Minimally Invasive Aspiration.

Computational and mathematical methods in medicine
The aim of this study was to investigate the therapeutic effect of minimally invasive aspiration on intracerebral hemorrhage (ICH) and the value of artificial intelligence algorithm combined with computed tomography (CT) image evaluation. Ninety-two ...

Deep Transfer Learning for Automatic Prediction of Hemorrhagic Stroke on CT Images.

Computational and mathematical methods in medicine
Intracerebral hemorrhage (ICH) is the most common type of hemorrhagic stroke which occurs due to ruptures of weakened blood vessel in brain tissue. It is a serious medical emergency issues that needs immediate treatment. Large numbers of noncontrast-...

Effect of an artificial intelligence-assisted tool on non-valvular atrial fibrillation anticoagulation management in primary care: protocol for a cluster randomized controlled trial.

Trials
BACKGROUND: Atrial fibrillation (AF) is one of the most common cardiac arrhythmia diseases. Thromboembolic prophylaxis plays an essential role in AF therapy, but at present, general practitioners (GPs) are presumed to lack the knowledge and enthusias...

Interpretability Analysis of One-Year Mortality Prediction for Stroke Patients Based on Deep Neural Network.

IEEE journal of biomedical and health informatics
Clinically, physicians collect the benchmark medical data to establish archives for a stroke patient and then add the follow up data regularly. It has great significance on prognosis prediction for stroke patients. In this paper, we present an interp...

Using Robot-Based Variables during Upper Limb Robot-Assisted Training in Subacute Stroke Patients to Quantify Treatment Dose.

Sensors (Basel, Switzerland)
In post-stroke motor rehabilitation, treatment dose description is estimated approximately. The aim of this retrospective study was to quantify the treatment dose using robot-measured variables during robot-assisted training in patients with subacute...

Application of the extended technology acceptance model to explore clinician likelihood to use robotics in rehabilitation.

Disability and rehabilitation. Assistive technology
PURPOSE: Evidence suggests that patients with upper limb impairment following a stroke do not receive recommended amounts of motor practice. Robotics provide a potential solution to address this gap, but clinical adoption is low. The aim of this stud...

Deep learning derived automated ASPECTS on non-contrast CT scans of acute ischemic stroke patients.

Human brain mapping
Ischemic stroke is the most common type of stroke, ranked as the second leading cause of death worldwide. The Alberta Stroke Program Early CT Score (ASPECTS) is considered as a systematic method of assessing ischemic change on non-contrast CT scans (...

Robot-Assisted Training as Self-Training for Upper-Limb Hemiplegia in Chronic Stroke: A Randomized Controlled Trial.

Stroke
BACKGROUND: This study aimed to examine whether robotic self-training improved upper-extremity function versus conventional self-training in mild-to-moderate hemiplegic chronic stroke patients.

Does frequent use of an exoskeletal upper limb robot improve motor function in stroke patients?

Disability and rehabilitation
PURPOSE: To determine how differences in frequency of the single-joint hybrid assistive limb (HAL-SJ) use affect the improvement of upper limb motor function and activities of daily living (ADL) in stroke patients.