AIMC Topic: Hemodynamics

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Rupture risk prediction of cerebral aneurysms using a novel convolutional neural network-based deep learning model.

Journal of neurointerventional surgery
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
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...

An Exploratory Study on the Relationship between Brachial Arterial Blood Flow and Cardiac Output.

Journal of healthcare engineering
BACKGROUND: We have obtained prospective clinical outcomes using the brachial artery largely, such as Korotkoff sound and vasomotor function measurement by ultrasound guidance to predict the prognosis of cardiovascular diseases. Very few reports on t...

Deep Learning Automated Background Phase Error Correction for Abdominopelvic 4D Flow MRI.

Radiology
Background Four-dimensional (4D) flow MRI has the potential to provide hemodynamic insights for a variety of abdominopelvic vascular diseases, but its clinical utility is currently impaired by background phase error, which can be challenging to corre...

Early prediction of hemodynamic interventions in the intensive care unit using machine learning.

Critical care (London, England)
BACKGROUND: Timely recognition of hemodynamic instability in critically ill patients enables increased vigilance and early treatment opportunities. We develop the Hemodynamic Stability Index (HSI), which highlights situational awareness of possible h...

A method of parameter estimation for cardiovascular hemodynamics based on deep learning and its application to personalize a reduced-order model.

International journal for numerical methods in biomedical engineering
Precise model personalization is a key step towards the application of cardiovascular physical models. In this manuscript, we propose to use deep learning (DL) to solve the parameter estimation problem in cardiovascular hemodynamics. Based on the con...

Assessing the Adequacy of Hemodialysis Patients via the Graph-Based Takagi-Sugeno-Kang Fuzzy System.

Computational and mathematical methods in medicine
Maintenance hemodialysis is the main method for the treatment of end-stage renal disease in China. The / value is the gold standard of hemodialysis adequacy. However, / requires repeated blood drawing and evaluation; it is hard to monitor dialysis ad...

Classification of impedance cardiography dZ/dt complex subtypes using pattern recognition artificial neural networks.

Biomedizinische Technik. Biomedical engineering
In impedance cardiography (ICG), the detection of dZ/dt signal (ICG) characteristic points, especially the X point, is a crucial step for the calculation of hemodynamic parameters such as stroke volume (SV) and cardiac output (CO). Unfortunately, for...