AIMC Topic: Death, Sudden, Cardiac

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Substrate Spatial Complexity Analysis for the Prediction of Ventricular Arrhythmias in Patients With Ischemic Cardiomyopathy.

Circulation. Arrhythmia and electrophysiology Mar 18, 2020
BACKGROUND: Transition zones between healthy myocardium and scar form a spatially complex substrate that may give rise to reentrant ventricular arrhythmias (VAs). We sought to assess the utility of a novel machine learning approach for quantifying 3-...
Risk Assessment Diagnosis, Computer-Assisted Imaging, Three-Dimensional United States Ventricular Function, Left Stroke Volume Middle Aged Registries Arrhythmias, Cardiac Heart Rate Myocardial Ischemia Contrast Media Magnetic Resonance Imaging Action Potentials Predictive Value of Tests Machine Learning Prognosis Retrospective Studies Female Risk Factors Aged Male Humans Death, Sudden, Cardiac Cardiomyopathies Fourier Analysis Gadolinium DTPA
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Improving the clinical understanding of hypertrophic cardiomyopathy by combining patient data, machine learning and computer simulations: A case study.

Morphologie : bulletin de l'Association des anatomistes Sep 27, 2019
Most patients with hypertrophic cardiomyopathy (HCM), the most common genetic cardiac disease, remain asymptomatic, but others may suffer from sudden cardiac death. A better identification of those patients at risk, together with a better understandi...
Asymptomatic Diseases Models, Cardiovascular Death, Sudden, Cardiac Heart Ventricles Patient Selection Cardiomyopathy, Hypertrophic Humans Machine Learning Computer Simulation Clinical Decision-Making Risk Factors Risk Assessment Electrocardiography Magnetic Resonance Imaging
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Machine learning for prediction of sudden cardiac death in heart failure patients with low left ventricular ejection fraction: study protocol for a retroprospective multicentre registry in China.

BMJ open May 16, 2019
INTRODUCTION: Left ventricular ejection fraction (LVEF) ≤35%, as current significant implantable cardioverter-defibrillator (ICD) indication for primary prevention of sudden cardiac death (SCD) in heart failure (HF) patients, has been widely recognis...
Humans Machine Learning Research Design Prospective Studies Retrospective Studies Multicenter Studies as Topic Registries Heart Failure Ventricular Function, Left Death, Sudden, Cardiac Stroke Volume China
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Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing.

International journal of medical informatics May 13, 2019
BACKGROUND: The management of hypertrophic cardiomyopathy (HCM) patients requires the knowledge of risk factors associated with sudden cardiac death (SCD). SCD risk factors such as syncope and family history of SCD (FH-SCD) as well as family history ...
Natural Language Processing Cardiomyopathy, Hypertrophic Death, Sudden, Cardiac Female Risk Factors Male Algorithms Middle Aged Prognosis Humans Electronic Health Records
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Artificial intelligence-augmented ECG assessment: The promise and the challenge.

Journal of cardiovascular electrophysiology Mar 11, 2019
Artificial Intelligence Electrocardiography Humans Death, Sudden, Cardiac
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Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology Mar 14, 2018
BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR)....
Regression Analysis Area Under Curve Heart Probability Risk ROC Curve Humans Machine Learning Reproducibility of Results Tomography, Emission-Computed, Single-Photon Support Vector Machine Algorithms Death, Sudden, Cardiac Aged Follow-Up Studies Female Male Middle Aged
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Optimizing the Primary Prevention of Sudden Cardiac Death in Patients With Heart Failure.

Journal of the American College of Cardiology Aug 5, 2025
Implantable cardioverter-defibrillators (ICDs) protect patients from sudden cardiac death (SCD). Landmark trials demonstrating their efficacy for primary prevention in patients with heart failure (HF) used reduced left ventricular ejection fraction (...
Heart Failure Defibrillators, Implantable Death, Sudden, Cardiac Primary Prevention Humans
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State-of-the-art analysis of electrocardiogram findings in sudden cardiac death.

Heart (British Cardiac Society) Jul 14, 2025
Sudden cardiac death (SCD) is a significant public health issue, and efforts to prevent it have involved the analysis of various modalities, including echocardiography, cardiac CT, cardiac MRI, genetic testing and ECG. The ECG, invented >100 years ag...
Humans Risk Assessment Artificial Intelligence Electrocardiography Risk Factors Death, Sudden, Cardiac
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Novel fusion-based time-frequency analysis for early prediction of sudden cardiac death from electrocardiogram signals.

Medical engineering & physics Jul 1, 2025
Sudden cardiac death (SCD) is one of the leading causes of global mortality, often occurring without warning and driven by complex cardiac dynamics. Despite significant advances in cardiovascular diagnostics, accurately predicting SCD at an early sta...
Male Middle Aged Deep Learning Time Factors Humans Female Electrocardiography Signal Processing, Computer-Assisted Death, Sudden, Cardiac
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Near-term prediction of sustained ventricular arrhythmias applying artificial intelligence to single-lead ambulatory electrocardiogram.

European heart journal Jun 2, 2025
BACKGROUND AND AIMS: Accurate near-term prediction of life-threatening ventricular arrhythmias would enable pre-emptive actions to prevent sudden cardiac arrest/death. A deep learning-enabled single-lead ambulatory electrocardiogram (ECG) may identif...
Death, Sudden, Cardiac Female Aged Male Middle Aged Risk Assessment Deep Learning Electrocardiography, Ambulatory Tachycardia, Ventricular Humans Artificial Intelligence Retrospective Studies
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