AIMC Topic: Heart Failure

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Multiple Plasma Biomarkers for Risk Stratification in Patients With Heart Failure and Preserved Ejection Fraction.

Journal of the American College of Cardiology
BACKGROUND: Better risk stratification strategies are needed to enhance clinical care and trial design in heart failure with preserved ejection fraction (HFpEF).

[Clinical research of target guided treatment of patients with severe heart failure under the guidance of pulse indicator continuous cardiac output].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To investigate the value of pulse indicator continuous cardiac output (PiCCO) monitoring in the treatment management of patients with severe heart failure.

20th Annual Feigenbaum Lecture: Echocardiography for Precision Medicine-Digital Biopsy to Deconstruct Biology.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Heart failure with preserved ejection fraction (HFpEF) is a complex, heterogeneous syndrome in need of improved classification given its high morbidity and mortality and few effective treatment options. HFpEF represents an ideal setting to examine th...

Predicting electrical storms by remote monitoring of implantable cardioverter-defibrillator patients using machine learning.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
AIMS: Electrical storm (ES) is a serious arrhythmic syndrome that is characterized by recurrent episodes of ventricular arrhythmias. Electrical storm is associated with increased mortality and morbidity despite the use of implantable cardioverter-def...

Dynamic Features Impact on the Quality of Chronic Heart Failure Predictive Modelling.

Studies in health technology and informatics
We study the way dynamics affects modelling in chronic heart failure (CHF) tasks. By dynamics we understand the patient history and the appearance of new events, states and variables changing in time. The goal is to understand what impact past data h...

The Mechanics of Machine Learning: From a Concept to Value.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography

Neural Networks for Prognostication of Patients With Heart Failure.

Circulation. Heart failure
Background Prognostication of heart failure patients from cardiopulmonary exercise test (CPET) currently involves simplification of complex time-series data into summary indices. We hypothesized that prognostication could be improved by considering t...

CHF Detection with LSTM Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Heart rate variability has been proven to be an effective prediction of risk of heart failure. The tradition method required manual feature extraction, thus may lead to potential error. In order to improve the robustness, a deep learning method based...