The use of sodium-glucose co-transporter 2 inhibitors to treat heart failure with preserved ejection fraction (HFpEF) is under investigation in ongoing clinical trials, but the exact mechanism of action is unclear. Here we aimed to use artificial int...
OBJECTIVES: The purpose of this study was to explore the prognostic significance of PTT and PBVi using an automated, inline method of estimation using CMR.
OBJECTIVES: The authors explored a deep neural network (DeepNN) model that integrates multidimensional echocardiographic data to identify distinct patient subgroups with heart failure with preserved ejection fraction (HFpEF).
We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram (ECG)-based, artificial intelligence (AI)-powered clinical decision support tool enables early diagnosis of low ejection fraction (EF), a condition that is unde...
Computer methods and programs in biomedicine
Mar 12, 2021
BACKGROUND: Despite the importance of stroke volume readings in understanding the work of the cardiovascular system in patients, its routine daily measurement outside of a hospital in the absence of special equipment presents a problem for a comprehe...
INTRODUCTION: Cardiac [F]FDG-PET is widely used for viability testing in patients with chronic ischemic heart disease. Guidelines recommend injection of 200-350 MBq [F]FDG, however, a reduction of radiation exposure has become increasingly important,...
Journal of cardiovascular electrophysiology
Feb 15, 2021
OBJECTIVE: This study aims to develop an artificial intelligence-based method to screen patients with left ventricular ejection fraction (LVEF) of 50% or lesser using electrocardiogram (ECG) data alone.
The aim of this study was to assess the accuracy of an algorithm for automated measurement of left ventricular ejection fraction (LVEF) available on handheld ultrasound devices (HUDs). One hundred twelve patients admitted to the cardiology department...