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Stroke

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Ultrafast MRI using deep learning echoplanar imaging for a comprehensive assessment of acute ischemic stroke.

European radiology
OBJECTIVES: Acute ischemic stroke (AIS) is an emergency requiring both fast and informative MR sequences. We aimed to assess the performance of an artificial intelligence-enhanced ultrafast (UF) protocol, compared to the reference protocol, in the AI...

Using Deep-Learning-Based Artificial Intelligence Technique to Automatically Evaluate the Collateral Status of Multiphase CTA in Acute Ischemic Stroke.

Tomography (Ann Arbor, Mich.)
BACKGROUND: Collateral status is an important predictor for the outcome of acute ischemic stroke with large vessel occlusion. Multiphase computed-tomography angiography (mCTA) is useful to evaluate the collateral status, but visual evaluation of this...

Effects of Upper Limb Robot-Assisted Rehabilitation Compared with Conventional Therapy in Patients with Stroke: Preliminary Results on a Daily Task Assessed Using Motion Analysis.

Sensors (Basel, Switzerland)
Robotic rehabilitation of the upper limb has demonstrated promising results in terms of the improvement of arm function in post-stroke patients. The current literature suggests that robot-assisted therapy (RAT) is comparable to traditional approaches...

Is the robotic rehabilitation that is added to intensive body rehabilitation effective for maximization of upper extremity motor recovery following a stroke? A randomized controlled study.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Trunk stabilization, which is a factor that directly affects the performance of affected upper-limb movements in stroke patients, is of critical importance in the performance of selective motor control.

Big Data in Stroke: How to Use Big Data to Make the Next Management Decision.

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics
The last decade has seen significant advances in the accumulation of medical data, the computational techniques to analyze that data, and corresponding improvements in management. Interventions such as thrombolytics and mechanical thrombectomy improv...

The effect of robot-assisted walking in different modalities on cardiorespiratory responses and energy consumption in patients with subacute stroke.

Neurological research
OBJECTIVES: The aim of our study was to evaluate the effect of robot-assisted walking in different modalities on cardiorespiratory responses and energy consumption in subacute stroke patients.

Efficacy of Robot-Assisted Training on Rehabilitation of Upper Limb Function in Patients With Stroke: A Systematic Review and Meta-analysis.

Archives of physical medicine and rehabilitation
OBJECTIVE: To systematically evaluate the effect of robot-assisted training (RAT) on upper limb function recovery in patients with stroke, providing the evidence-based medical basis for the clinical application of RAT.

SAN-Net: Learning generalization to unseen sites for stroke lesion segmentation with self-adaptive normalization.

Computers in biology and medicine
There are considerable interests in automatic stroke lesion segmentation on magnetic resonance (MR) images in the medical imaging field, as stroke is an important cerebrovascular disease. Although deep learning-based models have been proposed for thi...

DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy.

European radiology
OBJECTIVES: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombectomy. Deep learning has shown great promise in diagnostics but applications in video and interventional radiology lag behind. We aimed to develop a mode...