Cardiovascular

Strokes

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

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Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.

INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for sel...

Pleasant Stroke Touch on Human Back by a Human and a Robot.

Pleasant touching is an important aspect of social interactions that is widely used as a caregiving ...

Deep learning-based personalised outcome prediction after acute ischaemic stroke.

BACKGROUND: Whether deep learning models using clinical data and brain imaging can predict the long-...

Deep learning for collateral evaluation in ischemic stroke with imbalanced data.

PURPOSE: Collateral evaluation is typically done using visual inspection of cerebral images and thus...

Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke.

INTRODUCTION: Artificial intelligence (AI) has the potential to transform clinical decision-making a...

Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients.

PURPOSE: Multiple medical imaging modalities are used for clinical follow-up ischemic stroke analysi...

Head CT deep learning model is highly accurate for early infarct estimation.

Non-contrast head CT (NCCT) is extremely insensitive for early (< 3-6 h) acute infarct identificatio...

Multi-task deep learning for medical image computing and analysis: A review.

The renaissance of deep learning has provided promising solutions to various tasks. While convention...

Assessing electrocardiogram changes after ischemic stroke with artificial intelligence.

OBJECTIVE: Ischemic stroke (IS) with subsequent cerebrocardiac syndrome (CCS) has a poor prognosis. ...

Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning.

BACKGROUND: Accurate estimation of ischemic core on baseline imaging has treatment implications in p...

Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study.

OBJECTIVES: Accurate detection of carotid plaque using ultrasound (US) is essential for preventing s...

Immersive Virtual Reality during Robot-Assisted Gait Training: Validation of a New Device in Stroke Rehabilitation.

Background and objective: Duration of rehabilitation and active participation are crucial for gait r...

A Transferable Deep Learning Prognosis Model for Predicting Stroke Patients' Recovery in Different Rehabilitation Trainings.

Since the underlying mechanisms of neurorehabilitation are not fully understood, the prognosis of st...

Predicting Hypoperfusion Lesion and Target Mismatch in Stroke from Diffusion-weighted MRI Using Deep Learning.

Background Perfusion imaging is important to identify a target mismatch in stroke but requires contr...

Artificial intelligence for localization of the acute ischemic stroke by non-contrast computed tomography.

A non-contrast cranial computer tomography (ncCT) is often employed for the diagnosis of the early s...

Deep learning prediction of stroke thrombus red blood cell content from multiparametric MRI.

BACKGROUND AND PURPOSE: Thrombus red blood cell (RBC) content has been shown to be a significant fac...

Classification and Prediction on Hypertension with Blood Pressure Determinants in a Deep Learning Algorithm.

Few studies classified and predicted hypertension using blood pressure (BP)-related determinants in ...

An Ensemble of Deep Learning Enabled Brain Stroke Classification Model in Magnetic Resonance Images.

Brain stroke is a major cause of global death and it necessitates earlier identification process to ...

Expressions of serum adiponectin and visfatin in patients with hypertension in cerebrovascular accidents and analysis of risk factors.

OBJECTIVE: To determine the expressions of serum adiponectin and visfatin in patients with hypertens...

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