Cardiovascular

Strokes

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

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Gait Event Detection for Stroke Patients during Robot-Assisted Gait Training.

Functional electrical stimulation and robot-assisted gait training are techniques which are used in ...

A systematic review of machine learning models for predicting outcomes of stroke with structured data.

BACKGROUND AND PURPOSE: Machine learning (ML) has attracted much attention with the hope that it cou...

Accelerating massively parallel hemodynamic models of coarctation of the aorta using neural networks.

Comorbidities such as anemia or hypertension and physiological factors related to exertion can influ...

Effects of gait exercise assist robot (GEAR) on subjects with chronic stroke: A randomized controlled pilot trial.

OBJECTIVE: The aim of this study was to investigate whether gait training using the Gait Exercise As...

Mechanical heart valves and pregnancy: Issues surrounding anticoagulation. Experience from two obstetric cardiac centres.

BACKGROUND: Pregnant women with mechanical heart valves are at significant risk of obstetric/cardiac...

Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques.

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood ...

Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network.

In this paper, we demonstrate the feasibility and performance of deep residual neural networks for v...

Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. Ho...

Bioinspired Soft Microrobots with Precise Magneto-Collective Control for Microvascular Thrombolysis.

New-era soft microrobots for biomedical applications need to mimic the essential structures and coll...

Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand.

A robot-assisted hand is used for the rehabilitation of patients with impaired upper limb function, ...

SS-SWT and SI-CNN: An Atrial Fibrillation Detection Framework for Time-Frequency ECG Signal.

Atrial fibrillation is the most common arrhythmia and is associated with high morbidity and mortalit...

Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement.

The size of a device and its adaptability to human properties are important factors in developing a ...

Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers' performance.

PURPOSE: To evaluate the usefulness of deep learning-assisted diagnosis for identifying hyperdense m...

Detection of Atrial Fibrillation from Single Lead ECG Signal Using Multirate Cosine Filter Bank and Deep Neural Network.

Atrial fibrillation (AF) is a cardiac arrhythmia which is characterized based on the irregsular beat...

Acute and sub-acute stroke lesion segmentation from multimodal MRI.

BACKGROUND AND OBJECTIVE: Acute stroke lesion segmentation tasks are of great clinical interest as t...

Prediction of early neurological deterioration in acute minor ischemic stroke by machine learning algorithms.

OBJECTIVES: A significant proportion of patients with acute minor stroke have unfavorable functional...

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