Cardiovascular

Myocardial Infarction

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

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Showing 43-63 of 6,871 articles
Beyond Recanalization: Machine Learning-Based Insights into Post-Thrombectomy Vascular Morphology in Stroke Patients.

Many stroke patients have poor outcomes despite successful endovascular therapy (EVT). We hypothesiz...

Enhanced machine learning models for predicting three-year mortality in Non-STEMI patients aged 75 and above.

BACKGROUND: Non-ST segment elevation myocardial infarction (Non-STEMI) is a severe cardiovascular co...

A novel XAI framework for explainable AI-ECG using generative counterfactual XAI (GCX).

Generative Counterfactual Explainable Artificial Intelligence (XAI) offers a novel approach to under...

Machine learning evaluation model of pilot workload in a low-visibility environment.

To analyze the variation trend of pilots' workload in a low-visibility flight environment and then p...

Metabolomic biomarkers could be molecular clocks in timing stroke onset.

The preferred treatment for acute ischaemic stroke (AIS) is intravenous thrombolysis (IVT) administe...

DeepECG-Net: a hybrid transformer-based deep learning model for real-time ECG anomaly detection.

Real-time Electrocardiogram (ECG) anomaly detection is critical for accurate diagnosis and timely in...

Towards a dynamic model to estimate evolving risk of major bleeding after percutaneous coronary intervention.

While static risk models may identify key driving risk factors, the dynamic nature of risk requires ...

A Machine Learning Analysis of Physiological Monitoring Signals to Detect Small Airway Narrowing Due to Cold Air Exposure in Asthma.

Asthma is a chronic inflammatory disease of the small airways, affecting over 200 million people glo...

An enhanced deep learning framework for muscle artifact removal from ECG signal integrating resnet, GCAB, and BI-LSTM.

Electrocardiogram (ECG) signals are significantly distorted during recording by muscle artifact (MA)...

Electrocardiogram-Based Artificial Intelligence for Detection of Low Ejection Fraction: A Contemporary Review.

Artificial intelligence (AI) is transforming the role of electrocardiography (ECG) in cardiovascular...

From "time is brain" to "time is collaterals": updates on the role of cerebral collateral circulation in stroke.

BACKGROUND: Acute ischemic stroke (AIS) remains the leading cause of mortality and disability worldw...

Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits.

Electronic health records, biobanks, and wearable biosensors enable the collection of multiple healt...

Arrhythmia classification based on multi-input convolutional neural network with attention mechanism.

Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and ...

Artificial Intelligence-Enabled ECG to Detect Congenitally Corrected Transposition of the Great Arteries.

L-loop congenitally corrected transposition of the great arteries (ccTGA) is a rare congenital heart...

ECG-Based Detection of Acute Myocardial Infarction using a Wrist-Worn Device.

BACKGROUND: A wrist-worn wearable device for acquiring limb and chest ECG leads (wECG) may constitut...

Towards Artificial Intelligence-based Decision Support for Large-scale Screening for Atrial Fibrillation.

Atrial fibrillation is a prevalent cardiac arrhythmia, significantly increasing the risk of stroke, ...

A multimodal dataset for coronary microvascular disease biomarker discovery.

Coronary microvascular disease (CMD), particularly prevalent among women, is associated with increas...

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