AIMC Topic: Heart Failure

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An Automatic Approach Using ELM Classifier for HFpEF Identification Based on Heart Sound Characteristics.

Journal of medical systems Jul 15, 2019
Heart failure with preserved ejection fraction (HFpEF) is a complex and heterogeneous clinical syndrome. For the purpose of assisting HFpEF diagnosis, a non-invasive method using extreme learning machine and heart sound (HS) characteristics was provi...
Stroke Volume Image Processing, Computer-Assisted Logistic Models Heart Failure Markov Chains Heart Sounds Humans Machine Learning Algorithms
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Leveraging Machine Learning Techniques to Forecast Patient Prognosis After Percutaneous Coronary Intervention.

JACC. Cardiovascular interventions Jun 26, 2019
OBJECTIVES: This study sought to determine whether machine learning can be used to better identify patients at risk for death or congestive heart failure (CHF) rehospitalization after percutaneous coronary intervention (PCI).
Minnesota Humans Coronary Artery Disease Heart Failure Machine Learning Patient Readmission Decision Support Techniques Clinical Decision-Making Female Reproducibility of Results Risk Factors Aged Male Middle Aged Risk Assessment Time Factors Hospital Mortality Treatment Outcome Predictive Value of Tests Registries Percutaneous Coronary Intervention
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Neural networks versus Logistic regression for 30 days all-cause readmission prediction.

Scientific reports Jun 26, 2019
Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease progression and a source of considerable financial burden to the health...
Predictive Value of Tests Area Under Curve Heart Failure Probability Patient Readmission Middle Aged False Positive Reactions Deep Learning Risk ROC Curve Machine Learning Logistic Models Algorithms United States Female Humans Aged Neural Networks, Computer Male
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Using machine learning to characterize heart failure across the scales.

Biomechanics and modeling in mechanobiology Jun 25, 2019
Heart failure is a progressive chronic condition in which the heart undergoes detrimental changes in structure and function across multiple scales in time and space. Multiscale models of cardiac growth can provide a patient-specific window into the p...
Heart Ventricles Heart Failure Elasticity Systole Diastole Animals Male Swine Time Factors Myocardium Models, Cardiovascular Muscle Cells Machine Learning Computer Simulation Female
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Efficacy of Cardiac Rehabilitation with Assistance from Hybrid Assistive Limb in Patients with Chronic Heart Failure: Protocol for a Randomized Controlled Study.

Cardiology Jun 25, 2019
The hybrid assistive limb (HAL) provides motion assistance based on bioelectrical signals detected on the skin surface when muscle forces are generated. The lumbar-type HAL is expected to expand the therapeutic options for severe cardiac patients who...
Robotics Lumbosacral Region Humans Heart Failure Cardiac Rehabilitation Biomechanical Phenomena Lower Extremity Japan Clinical Trial Protocols as Topic Randomized Controlled Trials as Topic Exercise Therapy Chronic Disease Heart Rate
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Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.

Circulation. Arrhythmia and electrophysiology Jun 20, 2019
BACKGROUND: Cardiac resynchronization therapy (CRT) has significant nonresponse rates. We assessed whether machine learning (ML) could predict CRT response beyond current guidelines.
Retrospective Studies Clinical Decision-Making Female Risk Factors Aged Male Humans Machine Learning Decision Support Techniques Heart Failure Cardiac Resynchronization Therapy Progression-Free Survival Practice Guidelines as Topic Heart-Assist Devices Disease Progression Heart Transplantation Ventricular Function, Left Time Factors Ohio Stroke Volume Recovery of Function Baltimore Echocardiography Predictive Value of Tests Middle Aged Patient Selection Risk Assessment
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Computer-Aided Diagnosis and Clinical Trials of Cardiovascular Diseases Based on Artificial Intelligence Technologies for Risk-Early Warning Model.

Journal of medical systems Jun 13, 2019
The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical data. In order to achieve the regional medical and public health data analysis through ...
Chronic Disease Acute Disease Bayes Theorem Stroke Heart Failure Risk Assessment Severity of Illness Index Diagnosis, Computer-Assisted Logistic Models Support Vector Machine Data Mining Renal Insufficiency Humans Artificial Intelligence Prognosis
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Ventricular geometry-regularized QRSd predicts cardiac resynchronization therapy response: machine learning from crosstalk between electrocardiography and echocardiography.

The international journal of cardiovascular imaging May 18, 2019
Up to one-third of patients selected by current guidelines do not respond to cardiac resynchronization therapy (CRT), the aim of this study was to find out novel analytical approaches to improve pre-implantation CRT response prediction. Among 31 pre-...
Image Interpretation, Computer-Assisted Signal Processing, Computer-Assisted Humans Patient Selection Clinical Decision-Making Heart Failure Echocardiography Female Treatment Outcome Cardiac Resynchronization Therapy Middle Aged Aged Ventricular Remodeling Support Vector Machine Electrocardiography Aged, 80 and over Predictive Value of Tests Male Ventricular Function, Left
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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...
Retrospective Studies Ventricular Function, Left Stroke Volume China Multicenter Studies as Topic Registries Heart Failure Death, Sudden, Cardiac Humans Machine Learning Research Design Prospective Studies
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New Multiparametric Analysis of Cardiac Dyssynchrony: Machine Learning and Prediction of Response to CRT.

JACC. Cardiovascular imaging Apr 17, 2019
Cardiac Resynchronization Therapy Ventricular Dysfunction, Left Humans Image Interpretation, Computer-Assisted Decision Support Techniques Machine Learning Electrocardiography Treatment Outcome Retrospective Studies Predictive Value of Tests Clinical Decision-Making Signal Processing, Computer-Assisted Ventricular Function, Left Heart Failure Echocardiography
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