Cardiovascular

Strokes

Latest AI and machine learning research in strokes for healthcare professionals.

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Deep Learning Detection of Penumbral Tissue on Arterial Spin Labeling in Stroke.

Background and Purpose- Selection of patients with acute ischemic stroke for endovascular treatment ...

Analyzing brain structural differences associated with categories of blood pressure in adults using empirical kernel mapping-based kernel ELM.

BACKGROUND: Hypertension increases the risk of angiocardiopathy and cognitive disorder. Blood pressu...

Deep learning approaches for plethysmography signal quality assessment in the presence of atrial fibrillation.

OBJECTIVE: Photoplethysmography (PPG) monitoring has been implemented in many portable and wearable ...

Intracatheter Tissue Plasminogen Activator for Chronic Subdural Hematomas after Failed Bedside Twist Drill Craniostomy: A Retrospective Review.

Introduction Chronic subdural hematomas (cSDH) are common in neurosurgery with various symptoms and ...

Automatic segmentation of cerebral infarcts in follow-up computed tomography images with convolutional neural networks.

BACKGROUND AND PURPOSE: Infarct volume is a valuable outcome measure in treatment trials of acute is...

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

BACKGROUND: With the character of high incidence, high prevalence and high mortality, stroke has bro...

Highly precise risk prediction model for new-onset hypertension using artificial intelligence techniques.

Hypertension is a significant public health issue. The ability to predict the risk of developing hyp...

A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images.

Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of stroke surv...

Orbit image analysis machine learning software can be used for the histological quantification of acute ischemic stroke blood clots.

Our aim was to assess the utility of a novel machine learning software (Orbit Image Analysis) in the...

Recurrent ischemic stroke in patients with atrial fibrillation ablation and prior stroke: A study based on etiological classification.

BACKGROUND: Different subtypes of ischemic stroke may have different risk factors, clinical features...

Potential of machine learning methods to identify patients with nonvalvular atrial fibrillation.

Nonvalvular atrial fibrillation (NVAF) is associated with an increased risk of stroke however many ...

A novel computer-aided diagnosis system for the early detection of hypertension based on cerebrovascular alterations.

Hypertension is a leading cause of mortality in the USA. While simple tools such as the sphygmomanom...

Effectiveness of Intervention Based on End-effector Gait Trainer in Older Patients With Stroke: A Systematic Review.

OBJECTIVE: The objective of the article is to analyze the effects of the end-effector technology for...

[Predicting atrial fibrillation through a sinus-rhythm electrocardiogram; useful or not?].

In patients with cryptogenic stroke, the detection of atrial fibrillation (AF) is important, since i...

The neural and neurocomputational bases of recovery from post-stroke aphasia.

Language impairment, or aphasia, is a disabling symptom that affects at least one third of individua...

Data-driven analyses of motor impairments in animal models of neurological disorders.

Behavior provides important insights into neuronal processes. For example, analysis of reaching move...

Platelet-rich emboli are associated with von Willebrand factor levels and have poorer revascularization outcomes.

BACKGROUND AND AIMS: Platelets and von Willebrand factor (vWF) are key factors in thrombosis and thu...

Machine Learning-Based Forecast of Hemorrhagic Stroke Healthcare Service Demand considering Air Pollution.

This study aimed to forecast the pattern of the demand for hemorrhagic stroke healthcare services ba...

Development of a deep learning model to identify hyperdense MCA sign in patients with acute ischemic stroke.

PURPOSE: The aim of this study was to develop an interactive deep learning-assisted identification o...

Temporally downsampled cerebral CT perfusion image restoration using deep residual learning.

PURPOSE: Acute ischemic stroke is one of the most causes of death all over the world. Onset to treat...

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