Cardiovascular

Strokes

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

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Effect of robot-assisted gait training on improving cardiopulmonary function in stroke patients: a meta-analysis.

OBJECTIVE: Understanding the characteristics related to cardiorespiratory fitness after stroke can p...

Task-Oriented Training by a Personalized Electromyography-Driven Soft Robotic Hand in Chronic Stroke: A Randomized Controlled Trial.

BACKGROUND: Intensive task-oriented training has shown promise in enhancing distal motor function am...

Ensemble machine learning for predicting in-hospital mortality in Asian women with ST-elevation myocardial infarction (STEMI).

The accurate prediction of in-hospital mortality in Asian women after ST-Elevation Myocardial Infarc...

A machine learning analysis of predictors of future hypertension in a young population.

BACKGROUND: Early diagnosis of hypertension (HT) is crucial for preventing end-organ damage. This st...

A machine learning-based lung ultrasound algorithm for the diagnosis of acute heart failure.

Lung ultrasound (LUS) is an effective tool for diagnosing acute heart failure (AHF). However, severa...

Mitigating Trunk Compensatory Movements in Post-Stroke Survivors through Visual Feedback during Robotic-Assisted Arm Reaching Exercises.

Trunk compensatory movements frequently manifest during robotic-assisted arm reaching exercises for ...

Artificial intelligence to predict individualized outcome of acute ischemic stroke patients: The SIBILLA project.

INTRODUCTION: Formulating reliable prognosis for ischemic stroke patients remains a challenging task...

Telephone follow-up based on artificial intelligence technology among hypertension patients: Reliability study.

Artificial intelligence (AI) telephone is reliable for the follow-up and management of hypertensives...

Enhancing voxel-based dosimetry accuracy with an unsupervised deep learning approach for hybrid medical image registration.

BACKGROUND: Deformable registration is required to generate a time-integrated activity (TIA) map whi...

Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Increased left atrial volume and decreased left atrial function have long been associated with atria...

Predictive modelling and identification of key risk factors for stroke using machine learning.

Strokes are a leading global cause of mortality, underscoring the need for early detection and preve...

The independence of impairments in proprioception and visuomotor adaptation after stroke.

BACKGROUND: Proprioceptive impairments are common after stroke and are associated with worse motor r...

Risk Factors for Perinatal Arterial Ischemic Stroke: A Machine Learning Approach.

BACKGROUND AND OBJECTIVES: Perinatal arterial ischemic stroke (PAIS) is a focal vascular brain injur...

Effects of Rehabilitation Robot Training on Physical Function, Functional Recovery, and Daily Living Activities in Patients with Sub-Acute Stroke.

Stroke often results in sensory deficits, muscular weakness, and diminished postural control, thereb...

Deep-learning survival analysis for patients with calcific aortic valve disease undergoing valve replacement.

Calcification of the aortic valve (CAVDS) is a major cause of aortic stenosis (AS) leading to loss o...

A retrospective prognostic evaluation using unsupervised learning in the treatment of COVID-19 patients with hypertension treated with ACEI/ARB drugs.

INTRODUCTION: This study aimed to evaluate the prognosis of patients with COVID-19 and hypertension ...

Developing machine learning models to predict multi-class functional outcomes and death three months after stroke in Sweden.

Globally, stroke is the third-leading cause of mortality and disability combined, and one of the cos...

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