AIMC Topic: Myocardial Contraction
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Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning.
Scientific reports
Sep 14, 2020
Cardiac and aortic characteristics are crucial for cardiovascular disease detection. However, noninvasive estimation of aortic hemodynamics and cardiac contractility is still challenging. This paper investigated the potential of estimating aortic sys...
Machine-learning-based quality control of contractility of cultured human-induced pluripotent stem-cell-derived cardiomyocytes.
Biochemical and biophysical research communications
Apr 4, 2020
The precise and early assessment of cardiotoxicity is fundamental to bring forward novel drug candidates to the pharmaceutical market and to avoid their withdrawal from the market. Recent preclinical studies have attempted to use human-induced plurip...
Bioinspired Soft Robot with Incorporated Microelectrodes.
Journal of visualized experiments : JoVE
Feb 28, 2020
Bioinspired soft robotic systems that mimic living organisms using engineered muscle tissue and biomaterials are revolutionizing the current biorobotics paradigm, especially in biomedical research. Recreating artificial life-like actuation dynamics i...
Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram.
Nature medicine
Jan 7, 2019
Asymptomatic left ventricular dysfunction (ALVD) is present in 3-6% of the general population, is associated with reduced quality of life and longevity, and is treatable when found. An inexpensive, noninvasive screening tool for ALVD in the doctor's ...
Cardiac Phase Detection in Echocardiograms With Densely Gated Recurrent Neural Networks and Global Extrema Loss.
IEEE transactions on medical imaging
Dec 24, 2018
Accurate detection of end-systolic (ES) and end-diastolic (ED) frames in an echocardiographic cine series can be difficult but necessary pre-processing step for the development of automatic systems to measure cardiac parameters. The detection task is...
Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Sep 14, 2018
BACKGROUND: Cardiovascular resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction ...
Humans
Neural Networks, Computer
Databases, Factual
Observer Variation
Female
Myocardial Contraction
Deep Learning
Ventricular Function, Left
Automation
Reproducibility of Results
Predictive Value of Tests
Magnetic Resonance Imaging, Cine
Stroke Volume
Aged
Heart Diseases
Ventricular Function, Right
Middle Aged
Male
Image Interpretation, Computer-Assisted
Diagnosis of Heart Failure With Preserved Ejection Fraction: Machine Learning of Spatiotemporal Variations in Left Ventricular Deformation.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Aug 23, 2018
BACKGROUND: Stress testing helps diagnose heart failure with preserved ejection fraction (HFpEF), but there are no established criteria for quantifying left ventricular (LV) functional reserve. The aim of this study was to investigate whether compreh...
Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions.
International journal of computer assisted radiology and surgery
Jan 19, 2018
PURPOSE: Technical advancements have been part of modern medical solutions as they promote better surgical alternatives that serve to the benefit of patients. Particularly with cardiovascular surgeries, robotic surgical systems enable surgeons to per...
Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification.
Stem cell reports
Oct 12, 2017
Accurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC)-deriv...
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