AIMC Topic: Hemodynamics
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Segmenting 3D geometry of left coronary artery from coronary CT angiography using deep learning for hemodynamic evaluation.
Biomedical physics & engineering express
Nov 8, 2022
While coronary CT angiography (CCTA) is crucial for detecting several coronary artery diseases, it fails to provide essential hemodynamic parameters for early detection and treatment. These parameters can be easily obtained by performing computationa...
Fully-automated deep learning-based flow quantification of 2D CINE phase contrast MRI.
European radiology
Oct 29, 2022
OBJECTIVES: Time-resolved, 2D-phase-contrast MRI (2D-CINE-PC-MRI) enables in vivo blood flow analysis. However, accurate vessel contour delineation (VCD) is required to achieve reliable results. We sought to evaluate manual analysis (MA) compared to ...
A soft robotic sleeve mimicking the haemodynamics and biomechanics of left ventricular pressure overload and aortic stenosis.
Nature biomedical engineering
Sep 26, 2022
Preclinical models of aortic stenosis can induce left ventricular pressure overload and coarsely control the severity of aortic constriction. However, they do not recapitulate the haemodynamics and flow patterns associated with the disease. Here we r...
External validation of a machine learning model to predict hemodynamic instability in intensive care unit.
Critical care (London, England)
Jul 14, 2022
BACKGROUND: Early prediction model of hemodynamic instability has the potential to improve the critical care, whereas limited external validation on the generalizability. We aimed to independently validate the Hemodynamic Stability Index (HSI), a mul...
The Hemodynamic Parameters Values Prediction on the Non-Invasive Hydrocuff Technology Basis with a Neural Network Applying.
Sensors (Basel, Switzerland)
Jun 1, 2022
The task to develop a mechanism for predicting the hemodynamic parameters values based on non-invasive hydrocuff technology of a pulse wave signal fixation is described in this study. The advantages and disadvantages of existing methods of recording ...
Deep Learning Based Centerline-Aggregated Aortic Hemodynamics: An Efficient Alternative to Numerical Modeling of Hemodynamics.
IEEE journal of biomedical and health informatics
Apr 14, 2022
Image-based patient-specific modelling of hemodynamics are gaining increased popularity as a diagnosis and outcome prediction solution for a variety of cardiovascular diseases. While their potential to improve diagnostic capabilities and thereby clin...
Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome.
PloS one
Apr 7, 2022
Artificial intelligence and machine learning (AI/ML) is becoming increasingly more accessible to biomedical researchers with significant potential to transform biomedicine through optimization of highly-accurate predictive models and enabling better ...
AI-Enabled Advanced Development for Assessing Low Circulating Blood Volume for Emergency Medical Care: Comparison of Compensatory Reserve Machine-Learning Algorithms.
Sensors (Basel, Switzerland)
Mar 30, 2022
The application of artificial intelligence (AI) has provided new capabilities to develop advanced medical monitoring sensors for detection of clinical conditions of low circulating blood volume such as hemorrhage. The purpose of this study was to com...
Rupture risk prediction of cerebral aneurysms using a novel convolutional neural network-based deep learning model.
Journal of neurointerventional surgery
Feb 9, 2022
BACKGROUND: Cerebral aneurysms should be treated before rupture because ruptured aneurysms result in serious disability. Therefore, accurate prediction of rupture risk is important and has been estimated using various hemodynamic factors.
Effects of age, gender, and hemisphere on cerebrovascular hemodynamics in children and young adults: Developmental scores and machine learning classifiers.
PloS one
Feb 4, 2022
A constant blood supply to the brain is required for mental function. Research with Doppler ultrasonography has important clinical value and burgeoning potential with machine learning applications in studies predicting gestational age and vascular ag...
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