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...
BACKGROUND: A deep learning algorithm to detect low ejection fraction (EF) using routine 12-lead electrocardiogram (ECG) has recently been developed and validated. The algorithm was incorporated into the electronic health record (EHR) to automaticall...
We investigated clinical significance of cell-free DNA (cfDNA) in heart failure. This study enrolled 32 heart failure patients and 28 control subjects. Total cfDNA levels were not different between groups (P = 0.343). Bisulfite-digital polymerase cha...
Scandinavian cardiovascular journal : SCJ
Oct 18, 2019
In heart failure, invasive angiography is often employed to differentiate ischaemic from non-ischaemic cardiomyopathy. We aim to examine the predictive value of echocardiographic strain features alone and in combination with other features to differ...
Circulation. Cardiovascular quality and outcomes
Oct 15, 2019
BACKGROUND: We determined the impact of data volume and diversity and training conditions on recurrent neural network methods compared with traditional machine learning methods.
Utilizing clinical observational data to estimate individualized treatment effects (ITE) is a challenging task, as confounding inevitably exists in clinical data. Most of the existing models for ITE estimation tackle this problem by creating unbiased...
OBJECTIVES: This study sought to develop models for predicting mortality and heart failure (HF) hospitalization for outpatients with HF with preserved ejection fraction (HFpEF) in the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure with...
Journal of medical imaging and radiation sciences
Oct 3, 2019
BACKGROUND: Our previous work with iodine meta-iodobenzylguanidine (I-mIBG) radionuclide imaging among patients with cardiomyopathy reported limitations associated with the prognostic power of global parameters derived from planar imaging [1]. Employ...
OBJECTIVE: To develop and validate a novel, machine learning-derived model to predict the risk of heart failure (HF) among patients with type 2 diabetes mellitus (T2DM).
Unscheduled 30-day readmissions are a hallmark of Congestive Heart Failure (CHF) patients that pose significant health risks and escalate care cost. In order to reduce readmissions and curb the cost of care, it is important to initiate targeted inter...
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