Cardiovascular

Strokes

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

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Convolutional autoencoder-based deep learning for intracerebral hemorrhage classification using brain CT images.

Intracerebral haemorrhage (ICH) is a common form of stroke that affects millions of people worldwide...

Risk tools for predicting long-term sequelae based on symptom profiles after known and undetected SARS-CoV-2 infections in the population.

The aim was to determine the profile of long-term symptoms after known and undetected SARS-CoV-2 inf...

Harnessing the hybrid machine learning methods for stroke risk classification.

Stroke is a leading global cause of death, with 80% of cases considered preventable through early de...

An adaptive feedback system for the improvement of learners.

Teachers who are aware of their students' strengths and weakness can tailor their teaching methodolo...

Hybrid machine learning for real-time prediction of edema trajectory in large middle cerebral artery stroke.

In treating malignant cerebral edema after a large middle cerebral artery stroke, clinicians need qu...

Diagnostic challenges of carpal tunnel syndrome in patients with congenital thenar hypoplasia: a comprehensive review.

Carpal Tunnel Syndrome (CTS) is the most common entrapment neuropathy, frequently presenting with pa...

Transforming tabular data into images via enhanced spatial relationships for CNN processing.

Convolutional neural networks (CNNs), renowned for their efficiency in image analysis, have revoluti...

Direct evaluation of antiplatelet therapy in coronary artery disease by comprehensive image-based profiling of circulating platelets.

Coronary artery disease (CAD) is a leading cause of death globally. Antiplatelet therapy remains cru...

Prediction of Poor Visual Outcomes at Idiopathic Intracranial Hypertension Diagnosis Using a Supervised Machine Learning Algorithm.

BACKGROUND: Idiopathic intracranial hypertension (IIH) is a vision-threatening disorder mainly affec...

Hemostatic Activation Markers and Early Neurological Deterioration in Branch Atheromatous Disease-Related Stroke.

AIMS: Branch atheromatous disease (BAD)-related stroke, caused by atherosclerotic occlusion at the o...

Speckle pattern analysis with deep learning for low-cost stroke detection: a phantom-based feasibility study.

SIGNIFICANCE: Stroke is a leading cause of disability worldwide, necessitating rapid and accurate di...

Prediction of perimetric progression in ocular hypertension and open angle glaucoma based on corneal biomechanics.

PurposeTo identify parameters that are significant risk predictors of visual field (VF) progression ...

Invited Article: Al guided Dual Antiplatelet Therapy and Anticoagulation.

Artificial intelligence (AI) has emerged as a transformative tool in healthcare through data analysi...

Optimizing Stroke Risk Prediction: A Primary Dataset-Driven Ensemble Classifier With Explainable Artificial Intelligence.

BACKGROUND AND AIMS: Stroke remains a leading cause of mortality and long-term disability worldwide,...

Effects of exoskeleton rehabilitation robot training on neuroplasticity and lower limb motor function in patients with stroke.

BACKGROUND: Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower lim...

Multitask learning multimodal network for chronic disease prediction.

Chronic diseases are a critical focus in the management of elderly health. Early disease prediction ...

Optimizing stroke lesion segmentation: A dual-approach using Gaussian mixture models and nnU-Net.

Machine learning-based stroke lesion segmentation models are widely used in biomedical imaging, but ...

Detecting the left atrial appendage in CT localizers using deep learning.

Patients with cardioembolic stroke often undergo CT of the left atrial appendage (LAA), for example,...

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