AIMC Topic: Death, Sudden, Cardiac

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Deep learning methods for screening patients' S-ICD implantation eligibility.

Artificial intelligence in medicine Aug 9, 2021
Subcutaneous Implantable Cardioverter-Defibrillators (S-ICDs) are used for prevention of sudden cardiac death triggered by ventricular arrhythmias. T Wave Over Sensing (TWOS) is an inherent risk with S-ICDs which can lead to inappropriate shocks. A m...
Electrocardiography Mass Screening Arrhythmias, Cardiac Defibrillators, Implantable Humans Deep Learning Death, Sudden, Cardiac
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Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.

Circulation research Nov 10, 2020
RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.
Humans Neural Networks, Computer Phenotype Prospective Studies Prognosis Death, Sudden, Cardiac Electrophysiologic Techniques, Cardiac Male Tachycardia, Ventricular Middle Aged Time Factors Cardiomyopathies Risk Assessment Signal Processing, Computer-Assisted Support Vector Machine Ventricular Fibrillation Diagnosis, Computer-Assisted Myocardial Infarction Action Potentials Female Predictive Value of Tests Risk Factors Aged Aged, 80 and over
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Prediction of Sudden Cardiac Death Risk with a Support Vector Machine Based on Heart Rate Variability and Heartprint Indices.

Sensors (Basel, Switzerland) Sep 25, 2020
Most methods for sudden cardiac death (SCD) prediction require long-term (24 h) electrocardiogram recordings to measure heart rate variability (HRV) indices or premature ventricular complex indices (with the heartprint method). This work aimed to ide...
Male Ventricular Function, Left Stroke Volume Middle Aged Humans Female Aged Electrocardiography Support Vector Machine Heart Rate 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-...
Death, Sudden, Cardiac Action Potentials Predictive Value of Tests Registries Arrhythmias, Cardiac Cardiomyopathies Fourier Analysis Gadolinium DTPA Heart Rate Myocardial Ischemia Imaging, Three-Dimensional United States Contrast Media Magnetic Resonance Imaging Stroke Volume Middle Aged Risk Assessment Diagnosis, Computer-Assisted Humans Machine Learning Prognosis Retrospective Studies Aged Male Ventricular Function, Left Female Risk Factors
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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...
Humans Clinical Decision-Making Risk Factors Risk Assessment Machine Learning Computer Simulation Electrocardiography Magnetic Resonance Imaging Heart Ventricles Patient Selection Cardiomyopathy, Hypertrophic Asymptomatic Diseases Models, Cardiovascular Death, Sudden, Cardiac
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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...
Registries Heart Failure Death, Sudden, Cardiac Ventricular Function, Left Stroke Volume China Multicenter Studies as Topic Machine Learning Research Design Prospective Studies Retrospective Studies Humans
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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 ...
Electronic Health Records Cardiomyopathy, Hypertrophic Middle Aged Female Death, Sudden, Cardiac Humans Natural Language Processing Risk Factors Algorithms Male Prognosis
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Artificial intelligence-augmented ECG assessment: The promise and the challenge.

Journal of cardiovascular electrophysiology Mar 11, 2019
Death, Sudden, Cardiac Humans Artificial Intelligence Electrocardiography
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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)....
Death, Sudden, Cardiac ROC Curve Support Vector Machine Follow-Up Studies Regression Analysis Reproducibility of Results Probability Humans Risk Aged Machine Learning Tomography, Emission-Computed, Single-Photon Algorithms Male Female Middle Aged Area Under Curve Heart
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Late gadolinium enhancement imaging and sudden cardiac death.

European heart journal Sep 22, 2025
The prediction and management of sudden cardiac death risk continue to pose significant challenges in cardiovascular care despite advances in therapies over the last two decades. Late gadolinium enhancement (LGE) on cardiac magnetic resonance-a marke...
Magnetic Resonance Imaging Fibrosis Gadolinium Cardiomyopathies Death, Sudden, Cardiac Humans Machine Learning Contrast Media
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