Cardiovascular

Strokes

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

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Showing 190-210 of 2,996 articles
Integrating deep learning with ECG, heart rate variability and demographic data for improved detection of atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the ris...

Large Language Models' Ability to Assess Main Concepts in Story Retelling: A Proof-of-Concept Comparison of Human Versus Machine Ratings.

PURPOSE: Despite an abundance of manual, labor-intensive discourse analysis methods, there remains a...

Pathophysiological mechanisms of exertional dyspnea in people with cardiopulmonary disease: Recent advances.

Physical activity is a leading trigger of dyspnea in chronic cardiopulmonary diseases. Recently, the...

Machine learning combined with infrared spectroscopy for detection of hypertension pregnancy: towards newborn and pregnant blood analysis.

Biochemical changes in the cervix during labor are not well understood. This gap in knowledge is sig...

The effect of lower limb rehabilitation robot on lower limb -motor function in stroke patients: a systematic review and meta-analysis.

BACKGROUND: The assessment and enhancement of lower limb motor function in hemiplegic patients is of...

Microscope-Assisted Hypertensive Retinopathy Diagnosis Using Deep Learning Models.

The retina is the most crucial part of the human eye, and it can be affected due to hypertension. Ho...

Development of an artificial intelligence-enhanced warfarin interaction checker platform.

Warfarin is a common anticoagulant drug for thrombo-prophylaxis in stroke and venous thromboembolism...

Which approach better predicts diabetes: Traditional econometric methods or machine learning? Evidence from a cross-sectional study in South Korea.

To prevent chronic disease from getting worse, it is important to detect and predict it at an early ...

Identification of novel inflammatory response-related biomarkers in patients with ischemic stroke based on WGCNA and machine learning.

BACKGROUND: Ischemic stroke (IS) is one of the most common causes of disability in adults worldwide....

Radiomics-based MRI model to predict hypoperfusion in lacunar infarction.

BACKGROUND: Approximately 20-30 % of patients with acute ischemic stroke due to lacunar infarction e...

Effects of Robot-Assisted Therapy for Upper Limb Rehabilitation After Stroke: An Umbrella Review of Systematic Reviews.

BACKGROUND: Robotic rehabilitation, which provides a high-intensity, high-frequency therapy to impro...

A Machine Learning Prediction Model to Identify Individuals at Risk of 5-Year Incident Stroke Based on Retinal Imaging.

Stroke is a leading cause of death and disability in developed countries. We validated an AI-based p...

Machine learning prediction model for functional prognosis of acute ischemic stroke based on MRI radiomics of white matter hyperintensities.

OBJECTIVE: The purpose of the current study is to explore the value of a nomogram that integrates cl...

Predicting intra-abdominal hypertension using anthropometric measurements and machine learning.

Almost one in four critically ill patients suffer from intra-abdominal hypertension (IAH). Currently...

Robust resolution improvement of 3D UTE-MR angiogram of normal vasculatures using super-resolution convolutional neural network.

Contrast-enhanced UTE-MRA provides detailed angiographic information but at the cost of prolonged sc...

Leveraging machine learning for enhanced and interpretable risk prediction of venous thromboembolism in acute ischemic stroke care.

BACKGROUND: Venous thromboembolism (VTE) is a life-threatening complication commonly occurring after...

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