Cardiovascular

Myocardial Infarction

Latest AI and machine learning research in myocardial infarction for healthcare professionals.

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Deep Learning-Based Data Augmentation and Model Fusion for Automatic Arrhythmia Identification and Classification Algorithms.

Automated ECG-based arrhythmia detection is critical for early cardiac disease prevention and diagno...

Lightweight Multireceptive Field CNN for 12-Lead ECG Signal Classification.

The electrical activity produced during the heartbeat is measured and recorded by an ECG. Cardiologi...

Application of artificial intelligence techniques for automated detection of myocardial infarction: a review.

Myocardial infarction (MI) results in heart muscle injury due to receiving insufficient blood flow. ...

Adaptive wireless millirobotic locomotion into distal vasculature.

Microcatheters have enabled diverse minimally invasive endovascular operations and notable health be...

ECG Classification for Detecting ECG Arrhythmia Empowered with Deep Learning Approaches.

According to the World Health Organization (WHO) report, heart disease is spreading throughout the w...

Heartbeat Classification and Arrhythmia Detection Using a Multi-Model Deep-Learning Technique.

Cardiac arrhythmias pose a significant danger to human life; therefore, it is of utmost importance t...

Comparison of Deep Learning Algorithms in Predicting Expert Assessments of Pain Scores during Surgical Operations Using Analgesia Nociception Index.

There are many surgical operations performed daily in operation rooms worldwide. Adequate anesthesia...

Deep-Learning-Based Estimation of the Spatial QRS-T Angle from Reduced-Lead ECGs.

The spatial QRS-T angle is a promising health indicator for risk stratification of sudden cardiac de...

Machine Learning and Electrocardiography Signal-Based Minimum Calculation Time Detection for Blood Pressure Detection.

OBJECTIVE: Measurement and monitoring of blood pressure are of great importance for preventing disea...

Artificial intelligence fully automated myocardial strain quantification for risk stratification following acute myocardial infarction.

Feasibility of automated volume-derived cardiac functional evaluation has successfully been demonstr...

Classification of multi-lead ECG with deep residual convolutional neural networks.

. Automatic electrocardiogram (ECG) interpretation based on deep learning methods is attracting incr...

A Novel Deep Learning and Ensemble Learning Mechanism for Delta-Type COVID-19 Detection.

Recently, the novel coronavirus disease 2019 (COVID-19) has posed many challenges to the research co...

A Modified Deep Learning Framework for Arrhythmia Disease Analysis in Medical Imaging Using Electrocardiogram Signal.

Arrhythmias are anomalies in the heartbeat rhythm that occur occasionally in people's lives. These a...

An Automatic System for Continuous Pain Intensity Monitoring Based on Analyzing Data from Uni-, Bi-, and Multi-Modality.

Pain is a reliable indicator of health issues; it affects patients' quality of life when not well ma...

A Multimodal AI System for Out-of-Distribution Generalization of Seizure Identification.

Artificial intelligence (AI) and health sensory data-fusion hold the potential to automate many labo...

Artificial Intelligence-Enabled ECG: Physiologic and Pathophysiologic Insights and Implications.

Advancements in machine learning and computing methods have given new life and great excitement to o...

Automatic ECG classification and label quality in training data.

Within the PhysioNet/Computing in Cardiology Challenge 2021, we focused on the design of a machine l...

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