Cardiovascular

Strokes

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

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EMR-Based Phenotyping of Ischemic Stroke Using Supervised Machine Learning and Text Mining Techniques.

Ischemic stroke is a major cause of death and disability in adulthood worldwide. Because it has high...

Robot-assisted therapy for arm recovery for stroke patients: state of the art and clinical implication.

: Robot-assisted therapy is an emerging approach that performs highly repetitive, intensive, task or...

A proposed health monitoring system using fuzzy inference system.

Due to the busy schedule of every human being in today's world, consciousness towards one's health h...

Vitamin D insufficiency is associated with subclinical atherosclerosis in HIV-1-infected patients on combination antiretroviral therapy.

Vitamin D insufficiency has been associated with faster progression of atherosclerosis and increase...

RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields.

Segmentation of brain lesions from magnetic resonance images (MRI) is an important step for disease ...

In silico prediction of blood cholesterol levels from genotype data.

In this work we present a framework for blood cholesterol levels prediction from genotype data. The ...

Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry.

INTRODUCTION: Being able to predict functional outcomes after a stroke is highly desirable for clini...

Machine Learning for Detecting Early Infarction in Acute Stroke with Non-Contrast-enhanced CT.

Background Identifying the presence and extent of infarcted brain tissue at baseline plays a crucial...

Machine Learning Approach to Identify Stroke Within 4.5 Hours.

Background and Purpose- We aimed to investigate the ability of machine learning (ML) techniques anal...

Machine learning detection of Atrial Fibrillation using wearable technology.

BACKGROUND: Atrial Fibrillation is the most common arrhythmia worldwide with a global age adjusted p...

Predicting Chronic Subdural Hematoma Recurrence and Stroke Outcomes While Withholding Antiplatelet and Anticoagulant Agents.

The aging of the western population and the increased use of oral anticoagulation (OAC) and antipla...

Expression of Cytokines and Chemokines as Predictors of Stroke Outcomes in Acute Ischemic Stroke.

Ischemic stroke remains one of the most debilitating diseases and is the fifth leading cause of dea...

Bimodal Automated Carotid Ultrasound Segmentation Using Geometrically Constrained Deep Neural Networks.

For asymptomatic patients suffering from carotid stenosis, the assessment of plaque morphology is an...

Assessing stroke severity using electronic health record data: a machine learning approach.

BACKGROUND: Stroke severity is an important predictor of patient outcomes and is commonly measured w...

Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation.

IMPORTANCE: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its early ...

Reliability, validity and discriminant ability of a robotic device for finger training in patients with subacute stroke.

BACKGROUND: The majority of stroke survivors experiences significant hand impairments, as weakness a...

Real-Time Detection of Compensatory Patterns in Patients With Stroke to Reduce Compensation During Robotic Rehabilitation Therapy.

OBJECTIVES: Compensations are commonly employed by patients with stroke during rehabilitation withou...

Development of a Novel Prognostic Model to Predict 6-Month Swallowing Recovery After Ischemic Stroke.

Background and Purpose- The aim of this study was to explore clinical and radiological prognostic fa...

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