Cardiovascular

Strokes

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

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Assessing facial weakness in myasthenia gravis with facial recognition software and deep learning.

OBJECTIVE: Myasthenia gravis (MG) is an autoimmune disease leading to fatigable muscle weakness. Ext...

Label-free histological analysis of retrieved thrombi in acute ischemic stroke using optical diffraction tomography and deep learning.

For patients with acute ischemic stroke, histological quantification of thrombus composition provide...

Predicting blood pressure from face videos using face diagnosis theory and deep neural networks technique.

Hypertension is a major cause of cardiovascular diseases. Accurate and convenient measurement of blo...

Energy spectrum CT index-based machine learning model predicts the effect of intravenous thrombolysis in lower limbs.

To develop a noninvasive machine learning (ML) model based on energy spectrum computed tomography ve...

DGA3-Net: A parameter-efficient deep learning model for ASPECTS assessment for acute ischemic stroke using non-contrast computed tomography.

Detecting the early signs of stroke using non-contrast computerized tomography (NCCT) is essential f...

The effects of Robot-assisted gait training and virtual reality on balance and gait in stroke survivors: A randomized controlled trial.

BACKGROUND: Stroke survivors often experience balance and gait problems, which can affect their qual...

Automated Segmentation of Intracranial Thrombus on NCCT and CTA in Patients with Acute Ischemic Stroke Using a Coarse-to-Fine Deep Learning Model.

BACKGROUND AND PURPOSE: Identifying the presence and extent of intracranial thrombi is crucial in se...

Combating hypertension beyond genome-wide association studies: Microbiome and artificial intelligence as opportunities for precision medicine.

The single largest contributor to human mortality is cardiovascular disease, the top risk factor for...

Prototype development of bilateral arm mirror-like-robotic rehabilitation device for acute stroke patients.

During the early six months after the onset of a stroke, patients usually remain disabled with limbs...

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hyper...

Survey and Evaluation of Hypertension Machine Learning Research.

Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to co...

Gait training with a wearable powered robot during stroke rehabilitation: a randomized parallel-group trial.

BACKGROUND: We have developed a wearable rehabilitation robot, "curara®," and examined its immediate...

Body composition predicts hypertension using machine learning methods: a cohort study.

We used machine learning methods to investigate if body composition indices predict hypertension. Da...

Differential diagnosis of secondary hypertension based on deep learning.

Secondary hypertension is associated with higher risks of target organ damage and cardiovascular and...

Performance-Based Robotic Training in Individuals with Subacute Stroke: Differences between Responders and Non-Responders.

The high variability of upper limb motor recovery with robotic training (RT) in subacute stroke unde...

Classification of pulmonary sounds through deep learning for the diagnosis of interstitial lung diseases secondary to connective tissue diseases.

Early diagnosis of interstitial lung diseases secondary to connective tissue diseases is critical fo...

Deep learning prediction of motor performance in stroke individuals using neuroimaging data.

The degree of motor impairment and profile of recovery after stroke are difficult to predict for eac...

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