Cardiovascular

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

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Human-in-the-Loop Myoelectric Pattern Recognition Control of an Arm-Support Robot to Improve Reaching in Stroke Survivors.

The objective of this study was to assess the feasibility and efficacy of using real-time human-in-t...

Composite socio-environmental risk score for cardiovascular assessment: An explainable machine learning approach.

BACKGROUND: Cardiovascular disease (CVD) is the leading global cause of death, with socio-environmen...

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.

Hypertension presents the largest modifiable public health challenge due to its high prevalence, its...

Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection.

Uric acid is a key metabolic byproduct of purine degradation and plays a dual role in human health....

Establishment and validation of a ResNet-based radiomics model for predicting prognosis in cervical spinal cord injury patients.

Cervical spinal cord injury (cSCI) poses a significant challenge due to the unpredictable nature of ...

Abnormal heart sound recognition using SVM and LSTM models in real-time mode.

Cardiovascular diseases are non-communicable diseases that are considered the leading cause of death...

Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept Study.

INTRODUCTION: Timely thrombolytic therapy improves outcomes in acute ischemic stroke. Manual chart r...

Extraction of fetal heartbeat locations in abdominal phonocardiograms using deep attention transformer.

Assessing fetal health traditionally involves techniques like echocardiography, which require skille...

Automated detection of arrhythmias using a novel interpretable feature set extracted from 12-lead electrocardiogram.

The availability of large-scale electrocardiogram (ECG) databases and advancements in machine learni...

A computed tomography angiography-based radiomics model for prognostic prediction of endovascular abdominal aortic repair.

OBJECTIVE: This study aims to develop a radiomics machine learning (ML) model that uses preoperative...

Emerging rapid detection methods for the monitoring of cardiovascular diseases: Current trends and future perspectives.

Cardiovascular diseases (CVDs) persist as the foremost cause of global mortality, necessitating adva...

Multitarget Natural Compounds for Ischemic Stroke Treatment: Integration of Deep Learning Prediction and Experimental Validation.

Ischemic stroke's complex pathophysiology demands therapeutic approaches targeting multiple pathways...

Risk of bias assessment of post-stroke mortality machine learning predictive models: Systematic review.

BACKGROUND: Stroke is a major cause of mortality and permanent disability worldwide. Precise predict...

Deep learning-based automated segmentation of cardiac real-time MRI in non-human primates.

Advanced imaging techniques, like magnetic resonance imaging (MRI), have revolutionised cardiovascul...

A deep Bi-CapsNet for analysing ECG signals to classify cardiac arrhythmia.

- In recent times, the electrocardiogram (ECG) has been considered as a significant and effective sc...

Harnessing Electronic Health Records and Artificial Intelligence for Enhanced Cardiovascular Risk Prediction: A Comprehensive Review.

Electronic health records (EHR) have revolutionized cardiovascular disease (CVD) research by enablin...

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