AIMC Topic: Hemodynamics
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A review of machine learning methods for non-invasive blood pressure estimation.
Journal of clinical monitoring and computing
Sep 21, 2024
Blood pressure is a very important clinical measurement, offering valuable insights into the hemodynamic status of patients. Regular monitoring is crucial for early detection, prevention, and treatment of conditions like hypotension and hypertension,...
Physics-Informed Graph Neural Networks to solve 1-D equations of blood flow.
Computer methods and programs in biomedicine
Sep 20, 2024
BACKGROUND AND OBJECTIVE: Computational models of hemodynamics can contribute to optimizing surgical plans, and improve our understanding of cardiovascular diseases. Recently, machine learning methods have become essential to reduce the computational...
Physiological control for left ventricular assist devices based on deep reinforcement learning.
Artificial organs
Sep 17, 2024
BACKGROUND: The improvement of controllers of left ventricular assist device (LVAD) technology supporting heart failure (HF) patients has enormous impact, given the high prevalence and mortality of HF in the population. The use of reinforcement learn...
SAD: semi-supervised automatic detection of BOLD activations in high temporal resolution fMRI data.
Magma (New York, N.Y.)
Aug 29, 2024
OBJECTIVE: Despite the prevalent use of the general linear model (GLM) in fMRI data analysis, assuming a pre-defined hemodynamic response function (HRF) for all voxels can lead to reduced reliability and may distort the inferences derived from it. To...
A comparison of machine learning methods for recovering noisy and missing 4D flow MRI data.
International journal for numerical methods in biomedical engineering
Aug 28, 2024
Experimental blood flow measurement techniques are invaluable for a better understanding of cardiovascular disease formation, progression, and treatment. One of the emerging methods is time-resolved three-dimensional phase-contrast magnetic resonance...
Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Aug 8, 2024
BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data int...
Datasets as Topic
Blood Flow Velocity
Male
Aorta
Middle Aged
Humans
Reproducibility of Results
Perfusion Imaging
Regional Blood Flow
Hemodynamics
Case-Control Studies
Neural Networks, Computer
Aged
Image Interpretation, Computer-Assisted
Female
Deep Learning
Young Adult
Bicuspid Aortic Valve Disease
Aortic Valve
Adult
Predictive Value of Tests
Development of artificial intelligence-driven biosignal-sensitive cardiopulmonary resuscitation robot.
Resuscitation
Aug 8, 2024
AIM OF THE STUDY: We evaluated whether an artificial intelligence (AI)-driven robot cardiopulmonary resuscitation (CPR) could improve hemodynamic parameters and clinical outcomes.
Noninvasive and fast method of calculation for instantaneous wave-free ratio based on haemodynamics and deep learning.
Computer methods and programs in biomedicine
Jul 23, 2024
BACKGROUND AND OBJECTIVES: Instantaneous wave-free ratio (iFR) is a new invasive indicator of myocardial ischaemia, and its diagnostic performance is as good as the "gold standard" of myocardial ischaemia diagnosis: fractional flow reserve (FFR). iFR...
E-BDL: Enhanced Band-Dependent Learning Framework for Augmented Radar Sensing.
Sensors (Basel, Switzerland)
Jul 17, 2024
Radar sensors, leveraging the Doppler effect, enable the nonintrusive capture of kinetic and physiological motions while preserving privacy. Deep learning (DL) facilitates radar sensing for healthcare applications such as gait recognition and vital-s...
Machine learning models predict triage levels, massive transfusion protocol activation, and mortality in trauma utilizing patients hemodynamics on admission.
Computers in biology and medicine
Jul 16, 2024
BACKGROUND: The effective management of trauma patients necessitates efficient triaging, timely activation of Massive Blood Transfusion Protocols (MTP), and accurate prediction of in-hospital outcomes. Machine learning (ML) algorithms have emerged as...
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