AIMC Topic: Myocardium
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Machine Learning-Based Prediction of Myocardial Recovery in Patients With Left Ventricular Assist Device Support.
Circulation. Heart failure
Dec 24, 2021
BACKGROUND: Prospective studies demonstrate that aggressive pharmacological therapy combined with pump speed optimization may result in myocardial recovery in larger numbers of patients supported with left ventricular assist device (LVAD). This study...
A machine learning framework for the evaluation of myocardial rotation in patients with noncompaction cardiomyopathy.
PloS one
Nov 29, 2021
AIMS: Noncompaction cardiomyopathy (NCC) is considered a genetic cardiomyopathy with unknown pathophysiological mechanisms. We propose to evaluate echocardiographic predictors for rigid body rotation (RBR) in NCC using a machine learning (ML) based m...
Native-resolution myocardial principal Eulerian strain mapping using convolutional neural networks and Tagged Magnetic Resonance Imaging.
Computers in biology and medicine
Nov 18, 2021
BACKGROUND: Assessment of regional myocardial function at native pixel-level resolution can play a crucial role in recognizing the early signs of the decline in regional myocardial function. Extensive data processing in existing techniques limits the...
A deep learning approach to identify and segment alpha-smooth muscle actin stress fiber positive cells.
Scientific reports
Nov 8, 2021
Cardiac fibrosis is a pathological process characterized by excessive tissue deposition, matrix remodeling, and tissue stiffening, which eventually leads to organ failure. On a cellular level, the development of fibrosis is associated with the activa...
Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Oct 20, 2021
BACKGROUND: Attenuation correction can improve the quantitative accuracy of single-photon emission computed tomography (SPECT) images. Existing SPECT-only systems normally can only provide non-attenuation corrected (NC) images which are susceptible t...
Towards Intraoperative Quantification of Atrial Fibrosis Using Light-Scattering Spectroscopy and Convolutional Neural Networks.
Sensors (Basel, Switzerland)
Sep 9, 2021
Light-scattering spectroscopy (LSS) is an established optical approach for characterization of biological tissues. Here, we investigated the capabilities of LSS and convolutional neural networks (CNNs) to quantitatively characterize the composition a...
Decoding empagliflozin's molecular mechanism of action in heart failure with preserved ejection fraction using artificial intelligence.
Scientific reports
Jun 8, 2021
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...
Machine learning prediction of sleep stages in dairy cows from heart rate and muscle activity measures.
Scientific reports
May 25, 2021
Sleep is important for cow health and shows promise as a tool for assessing welfare, but methods to accurately distinguish between important sleep stages are difficult and impractical to use with cattle in typical farm environments. The objective of ...
Editorial for "Improved Quantification of Myocardium Scar in Late Gadolinium Enhancement Images: Deep Learning Based Image Fusion Approach".
Journal of magnetic resonance imaging : JMRI
Mar 29, 2021
A Myocardial Segmentation Method Based on Adversarial Learning.
BioMed research international
Feb 26, 2021
Congenital heart defects (CHD) are structural imperfections of the heart or large blood vessels that are detected around birth and their symptoms vary wildly, with mild case patients having no obvious symptoms and serious cases being potentially life...
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