Cardiovascular

Myocardial Infarction

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

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Deep learning approach for automatic assessment of schizophrenia and bipolar disorder in patients using R-R intervals

Schizophrenia and bipolar disorder are severe mental illnesses that significantly impact quality of ...

Evaluating biomedical feature fusion on machine learning’s predictability and interpretability of COVID-19 severity types

Accurately differentiating severe from non-severe COVID-19 clinical types is critical for the health...

Interethnic Validation of Artificial Intelligence for prediction of Atrial Fibrillation Using Sinus Rhythm Electrocardiogram

Previous research has demonstrated acceptable diagnostic accuracy of AI-enabled sinus rhythm (SR) el...

Emulating Clinical Trials with the Mayo Clinic Platform: Cardiovascular Research Perspective

Randomized controlled trials (RCTs) provide the highest level of clinical evidence but are often lim...

Integrating AI-ECG and Point-of-Care Cardiac Ultrasound for Screening Structural Heart Disease: A Proof-of-Concept Study

Early structural heart disease (SHD) detection is crucial for improving prognostic outcomes, but wid...

Understanding the Feasibility of Computer Vision in Diagnosing Respiratory Infections in Pediatric Emergency Rooms

Respiratory infections are a leading cause of pediatric emergency visits globally, requiring timely ...

Identification of Hypertrophic Cardiomyopathy on Electrocardiographic Images with Deep Learning

Hypertrophic cardiomyopathy (HCM) is frequently underdiagnosed. While deep learning (DL) models usin...

Artificial intelligence-enhanced Electrocardiography Score for Perioperative Risk Assessment in Non-cardiac Surgery

The role of electrocardiography (ECG) has been limited in the preoperative risk evaluation in noncar...

A Standard Framework for Converting Coronary Angiography Reports into Machine-Readable Format Using Large Language Models

Coronary angiography (CAG) reports contain many details about coronary anatomy, lesion characteristi...

AI-MI: A Deep Learning Model to Predict Actionable Acute Coronary Syndrome Using 12-Lead ECGs

Chest pain is among the most common chief complaints in Emergency Departments (EDs), and differentia...

DeepDrug2: A Germline-focused Graph Neural Network Framework for Alzheimer’s Drug Repurposing Validated by Electronic Health Records

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with limited therapeutic options. T...

Detection of Atrial Fibrillation with a Hybrid Deep Learning Model and Time-Frequency Representations

Atrial fibrillation (AF), a common cardiac arrhythmia, can lead to severe complications, emphasizing...

Wearable-Echo-FM: An ECG-echo foundation model for single lead electrocardiography

Artificial intelligence (AI) models can now detect patterns of structural heart diseases (SHDs) from...

DWI and Clinical Characteristics Correlations in Acute Ischemic Stroke After Thrombolysis

Magnetic Resonance Diffusion-Weighted Imaging (DWI) is a crucial tool for diagnosing acute ischemic ...

The miniECG: Enabling interpretable detection of amplitude and intraventricular conduction ECG-abnormalities with a novel ECG device

The miniECG, a smartphone-sized, multi-lead device, offers a simple and fast alternative to the 12-l...

AI-Driven Personalization of Dual Antiplatelet Therapy Duration Post-PCI: A Novel Approach Balancing Ischemic and Bleeding Risks

Precision-guided dual antiplatelet therapy (DAPT) duration post-percutaneous coronary intervention (...

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