AIMC Topic: Heart Valve Diseases

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The Emerging Role of Artificial Intelligence in Valvular Heart Disease.

Heart failure clinics Apr 7, 2023
Valvular heart disease (VHD) is a morbid condition in which timely identification and evidence-based treatments can lead to improved outcomes. Artificial intelligence broadly refers to the ability for computers to perform tasks and problem solve like...
Artificial Intelligence Machine Learning Prospective Studies Heart Valve Diseases Humans
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A lightweight hybrid deep learning system for cardiac valvular disease classification.

Scientific reports Aug 22, 2022
Cardiovascular diseases (CVDs) are a prominent cause of death globally. The introduction of medical big data and Artificial Intelligence (AI) technology encouraged the effort to develop and deploy deep learning models for distinguishing heart sound a...
Artificial Intelligence Deep Learning Mitral Valve Insufficiency Humans Heart Valve Diseases Mitral Valve Prolapse
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A deep learning-based automatic analysis of cardiovascular borders on chest radiographs of valvular heart disease: development/external validation.

European radiology Oct 13, 2021
OBJECTIVES: Cardiovascular border (CB) analysis is the primary method for detecting and quantifying the severity of cardiovascular disease using posterior-anterior chest radiographs (CXRs). This study aimed to develop and validate a deep learning-bas...
Humans Radiography Algorithms Heart Valve Diseases Reproducibility of Results Deep Learning
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The role of robotic technology in minimally invasive surgery for mitral valve disease.

Expert review of medical devices Aug 18, 2021
INTRODUCTION: Robotic mitral valve surgery has developed for more than 20 years. The main purpose of robotic assistance is to use multiwristed instruments for surgical endothoracic maneuvers on the mitral valve without opening the chest. The surgeon ...
Mitral Valve Insufficiency Heart Valve Diseases Minimally Invasive Surgical Procedures Humans Cardiac Surgical Procedures Robotics Mitral Valve
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Ensemble machine learning prediction and variable importance analysis of 5-year mortality after cardiac valve and CABG operations.

Scientific reports Feb 10, 2021
Despite having a similar post-operative complication profile, cardiac valve operations are associated with a higher mortality rate compared to coronary artery bypass grafting (CABG) operations. For long-term mortality, few predictors are known. In th...
Aged Sensitivity and Specificity Male Machine Learning Algorithms Female Cardiac Surgical Procedures Probability Heart Valve Diseases Risk Assessment Cohort Studies Time Factors Humans Coronary Artery Bypass
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Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease.

BMC cardiovascular disorders Jan 28, 2021
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia with poorly understood mechanisms. We aimed to investigate the biological mechanism of AF and to discover feature genes by analyzing multi-omics data and by applying a machine learnin...
Bayes Theorem Atrial Fibrillation Heart Atria Heart Valve Diseases Oligonucleotide Array Sequence Analysis Proteomics Female Signal Transduction Male Databases, Genetic Middle Aged Humans Protein Interaction Maps Gene Expression Profiling Machine Learning Transcriptome Gene Regulatory Networks Case-Control Studies Genetic Association Studies
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Machine learning-based risk prediction of intrahospital clinical outcomes in patients undergoing TAVI.

Clinical research in cardiology : official journal of the German Cardiac Society Jun 24, 2020
BACKGROUND: Currently, patient selection in TAVI is based upon a multidisciplinary heart team assessment of patient comorbidities and surgical risk stratification. In an era of increasing need for precision medicine and quickly expanding TAVI indicat...
Postoperative Complications Time Factors Hospital Mortality Aortic Valve Inpatients Cause of Death Survival Rate Male Risk Assessment Humans Female Machine Learning Risk Factors Retrospective Studies Aged, 80 and over Morbidity Transcatheter Aortic Valve Replacement Heart Valve Diseases Germany
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Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
While natural language processing (NLP) of unstructured clinical narratives holds the potential for patient care and clinical research, portability of NLP approaches across multiple sites remains a major challenge. This study investigated the portabi...
Health Information Interoperability Electronic Health Records Echocardiography Narration Humans Natural Language Processing Retrospective Studies Heart Heart Valve Diseases
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Continuous-Flow Left Ventricular Assist Devices and Valvular Heart Disease: A Comprehensive Review.

The Canadian journal of cardiology Nov 25, 2019
Mechanical circulatory support with implantable durable continuous-flow left ventricular assist devices (CF-LVADs) represents an established surgical treatment option for patients with advanced heart failure refractory to guideline-directed medical t...
Humans Heart-Assist Devices Heart Failure Heart Valve Diseases
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Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences.

Nature communications Jul 15, 2019
Biomedical repositories such as the UK Biobank provide increasing access to prospectively collected cardiac imaging, however these data are unlabeled, which creates barriers to their use in supervised machine learning. We develop a weakly supervised ...
Machine Learning Magnetic Resonance Imaging Aortic Valve Humans Neural Networks, Computer Supervised Machine Learning Heart Diseases Heart Valve Diseases
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