Predicting Stroke and Mortality in Mitral Regurgitation: A Gradient Boosting Approach
Introduction We hypothesized that an interpretable gradient boosting machine (GBM) model
considering comorbidities, P-wave and echocardiographic measurements, can better predict …
considering comorbidities, P-wave and echocardiographic measurements, can better predict …
[HTML][HTML] Predicting stroke and mortality in mitral regurgitation: a machine learning approach
Introduction We hypothesized that an interpretable gradient boosting machine (GBM) model
considering comorbidities, P-wave and echocardiographic measurements, can better predict …
considering comorbidities, P-wave and echocardiographic measurements, can better predict …
Multi‐parametric system for risk stratification in mitral regurgitation: A multi‐task Gaussian prediction approach
Background We hypothesized that a multi‐parametric approach incorporating medical
comorbidity information, electrocardiographic P‐wave indices, echocardiographic …
comorbidity information, electrocardiographic P‐wave indices, echocardiographic …
Data-driven mortality risk prediction of severe degenerative mitral regurgitation patients undergoing mitral valve surgery
Aims The outcomes of mitral valve replacement/repair (MVR) in severe degenerative mitral
regurgitation (MR) patients depend on various risk factors. We aimed to develop a risk …
regurgitation (MR) patients depend on various risk factors. We aimed to develop a risk …
An Automated Machine Learning–Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading
Background Considering the high prevalence of mitral regurgitation (MR) and the highly
subjective, variable MR severity reporting, an automated tool that could screen patients for …
subjective, variable MR severity reporting, an automated tool that could screen patients for …
Supervised learning-derived tailored risk-stratification in patients with severe secondary mitral regurgitation
G Heitzinger, G Spinka, S Prausmueller… - European Heart …, 2022 - academic.oup.com
Background Mitral regurgitation secondary to heart failure (sMR) has considerable impact
on quality of life, heart failure (HF) rehospitalizations and mortality. A diverse burden of …
on quality of life, heart failure (HF) rehospitalizations and mortality. A diverse burden of …
Machine learning as a new frontier in mitral valve surgical strategy
R Nedadur, B Wang, W Tsang - Journal of Cardiac Surgery, 2022 - Wiley Online Library
Background One of the surgical options available for ischemic mitral regurgitation (MR) is
mitral valve repair but is limited by recurrent regurgitation as it is experienced by a significant …
mitral valve repair but is limited by recurrent regurgitation as it is experienced by a significant …
Tailored risk stratification in severe mitral regurgitation and heart failure using supervised learning techniques
G Heitzinger, G Spinka, S Prausmüller, N Pavo… - JACC: Advances, 2022 - jacc.org
Background Secondary mitral regurgitation (sMR) in the setting of heart failure (HF) has
considerable impact on quality of life, HF rehospitalizations, and mortality. Identification of …
considerable impact on quality of life, HF rehospitalizations, and mortality. Identification of …
Understanding post-surgical decline in left ventricular function in primary mitral regurgitation using regression and machine learning models
Background Class I echocardiographic guidelines in primary mitral regurgitation (PMR) risks
left ventricular ejection fraction (LVEF)< 50% after mitral valve surgery even with pre-surgical …
left ventricular ejection fraction (LVEF)< 50% after mitral valve surgery even with pre-surgical …
Integrating echocardiography parameters with explainable artificial intelligence for data-driven clustering of primary mitral regurgitation phenotypes
Background Primary mitral regurgitation (MR) is a heterogeneous clinical disease requiring
integration of echocardiographic parameters using guideline-driven recommendations to …
integration of echocardiographic parameters using guideline-driven recommendations to …