AIMC Topic: Cardiomyopathy, Hypertrophic

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Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles.

Methods of information in medicine Feb 20, 2020
BACKGROUND:  Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previousl...
Tropomyosin Diagnosis, Differential Humans Signal Processing, Computer-Assisted Machine Learning Long QT Syndrome Algorithms Calcium Carrier Proteins Cardiomyopathy, Hypertrophic
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Three-dimensional Deep Convolutional Neural Networks for Automated Myocardial Scar Quantification in Hypertrophic Cardiomyopathy: A Multicenter Multivendor Study.

Radiology Nov 12, 2019
Background Cardiac MRI late gadolinium enhancement (LGE) scar volume is an important marker for outcome prediction in patients with hypertrophic cardiomyopathy (HCM); however, its clinical application is hindered by a lack of measurement standardizat...
Humans Neural Networks, Computer Retrospective Studies Child Imaging, Three-Dimensional Magnetic Resonance Imaging Cicatrix Young Adult Myocardium Adult Heart Male Female Image Interpretation, Computer-Assisted Middle Aged Reproducibility of Results Cardiomyopathy, Hypertrophic Adolescent Aged Aged, 80 and over
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Assessment of ventricular tachyarrhythmia in patients with hypertrophic cardiomyopathy with machine learning-based texture analysis of late gadolinium enhancement cardiac MRI.

Diagnostic and interventional imaging Nov 11, 2019
OBJECTIVE: To assess the diagnostic value of machine learning-based texture feature analysis of late gadolinium enhancement images on cardiac magnetic resonance imaging (MRI) for assessing the presence of ventricular tachyarrhythmia (VT) in patients ...
Young Adult Adult Male Middle Aged Contrast Media Machine Learning Retrospective Studies Female Aged Tachycardia, Ventricular Cardiac Imaging Techniques Magnetic Resonance Imaging Cardiomyopathy, Hypertrophic Gadolinium Image Enhancement Humans
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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...
Electrocardiography Magnetic Resonance Imaging Heart Ventricles Patient Selection Cardiomyopathy, Hypertrophic Asymptomatic Diseases Models, Cardiovascular Death, Sudden, Cardiac Machine Learning Computer Simulation Clinical Decision-Making Risk Factors Risk Assessment Humans
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Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning.

Molecular & cellular proteomics : MCP Jun 26, 2019
Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a significant number of high risk cases still go undetected until a sudden cardiac death (SCD) event....
Cardiomyopathy, Hypertrophic Hypertrophy, Left Ventricular Sarcomeres Prospective Studies Adult Biomarkers Male Female Middle Aged Humans Aged Peptides Machine Learning Young Adult Phenotype Severity of Illness Index Case-Control Studies Proteomics Predictive Value of Tests Mutation
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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 ...
Algorithms Prognosis Electronic Health Records Female Death, Sudden, Cardiac Risk Factors Humans Male Middle Aged Natural Language Processing Cardiomyopathy, Hypertrophic
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Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy (HCM-VAr-Risk Model).

The American journal of cardiology Feb 27, 2019
Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines or the HCM Risk-SCD model (C-index ∼...
Cardiomyopathy, Hypertrophic Tachycardia, Ventricular Echocardiography, Stress Magnetic Resonance Imaging, Cine Humans Risk Assessment Electrocardiography Predictive Value of Tests Registries Female Reproducibility of Results Risk Factors Machine Learning Male Middle Aged Prognosis Retrospective Studies Electronic Health Records
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Automated Cardiac MR Scar Quantification in Hypertrophic Cardiomyopathy Using Deep Convolutional Neural Networks.

JACC. Cardiovascular imaging Aug 15, 2018
Image Interpretation, Computer-Assisted Cardiomyopathy, Hypertrophic Automation Proof of Concept Study Magnetic Resonance Imaging Predictive Value of Tests Cicatrix Myocardium Humans Deep Learning
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Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks.

Medical image analysis May 22, 2018
Pixelwise segmentation of the left ventricular (LV) myocardium and the four cardiac chambers in 2-D steady state free precession (SSFP) cine sequences is an essential preprocessing step for a wide range of analyses. Variability in contrast, appearanc...
Humans Image Processing, Computer-Assisted Neural Networks, Computer Cardiomyopathy, Hypertrophic Algorithms Cardiac Imaging Techniques
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Artificial intelligence-enhanced electrocardiogram diastolic function grade predicts post-septal myectomy mortality in hypertrophic cardiomyopathy.

The Journal of thoracic and cardiovascular surgery Dec 1, 2025
BACKGROUNDS: Diastolic dysfunction is an important pathophysiologic feature of hypertrophic cardiomyopathy that is often challenging to determine noninvasively. This study investigated whether a novel artificial intelligence-enabled electrocardiograp...
Aged Male Ventricular Function, Left Middle Aged Risk Assessment Predictive Value of Tests Artificial Intelligence Cardiac Surgical Procedures Deep Learning Cardiomyopathy, Hypertrophic Retrospective Studies Humans Diastole Female Length of Stay Heart Septum Risk Factors Time Factors Electrocardiography Treatment Outcome
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