BACKGROUND: Mortality remains unacceptably high in patients with heart failure and reduced left ventricular ejection fraction (LVEF) despite advances in therapeutics. We hypothesised that a novel artificial intelligence approach could better assess m...
BACKGROUND: Heart failure (HF) is a leading cause of cardiac morbidity among women, whose risk factors differ from those in men. We used machine-learning approaches to develop risk- prediction models for incident HF in a cohort of postmenopausal wome...
AIMS: Individual risk stratification is a fundamental strategy in managing patients with heart failure (HF). Artificial intelligence, particularly machine learning (ML), can develop superior models for predicting the prognosis of HF patients, and adm...
OBJECTIVE: The role of deep learning-based echocardiography in the diagnosis and evaluation of the effects of routine anti-heart-failure Western medicines was investigated in elderly patients with acute left heart failure (ALHF).
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Aug 7, 2021
In this study, we investigated the effect of principal component analysis (PCA) in congestive heart failure (CHF) diagnosis using various machine learning algorithms from 5-min HRV data. The extracted 59 heart rate variability (HRV) features consist ...
The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultrasound images, which was used for the research on elderly patients with chronic heart failure (CHF) complicated with sarcopenia, so as to analyze the ...
Cardiovascular engineering and technology
Jul 14, 2021
PURPOSE: In clinical practice, many patients with right heart failure (RHF) have elevated pulmonary artery pressures and increased afterload on the right ventricle (RV). In this study, we evaluated the feasibility of RV augmentation using a soft robo...
Clinical research in cardiology : official journal of the German Cardiac Society
Jul 14, 2021
OBJECTIVE: Machine learning (ML) algorithm can improve risk prediction because ML can select features and segment continuous variables effectively unbiased. We generated a risk score model for mortality with ML algorithms in East-Asian patients with ...
BACKGROUND: Heart failure (HF) is associated with chronic inflammation, which is adversely associated with survival. Although sex-related differences in inflammation have been described in patients with HF, whether sex-related differences in inflamma...
Heart Failure (HF) is a major cause of morbidity and mortality in the US. With aging of the US population, the public health burden of HF is enormous. We aimed to develop an ensemble prediction model for 30-day mortality after discharge using machine...