Bahetihazi Maidu on Muck Rack

Bahetihazi Maidu

As seen in: BioRxiv, RadcliffeCardiology.com
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Articles

Super-resolution Left Ventricular Flow and Pressure Mapping by Navier-Stokes-Informed Neural Networks

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By Bahetihazi Maidu, Pablo Martinez-Legazpi, Manuel Guerrero-Hurtado, Cathleen M. Nguyen
| BioRxiv
Abstract Intraventricular vector flow mapping (VFM) is a growingly adopted echocardiographic modality that derives time-resolved two-dimensional flow maps in the left ventricle (LV) from color-Doppler sequences. Current VFM models rely on kinematic constraints arising from planar flow incompressibility. However, these models are not informed by crucial information about flow physics; most notably the pressure and shear forces within the fluid and the resulting accelerations.
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Machine Learning and the Conundrum of Stroke Risk Prediction

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By Yaacoub Chahine, Matthew J Magoon, Bahetihazi Maidu, Patrick Boyle
| aerjournal.com
Stroke is a leading cause of death and permanent disability worldwide.1 Ischaemic stroke is the most common stroke variety, comprising more than 80% of strokes in the US.2 One mechanism of ischaemic stroke is atherosclerosis in the extracranial and intracranial arteries, with plaque rupture leading to thrombosis.
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Bahetihazi Maidu

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By Yaacoub Chahine, Matthew J Magoon, Bahetihazi Maidu
| RadcliffeCardiology.com Verified
Published content on this site is for information purposes and is not a substitute for professional medical advice. Where views/opinions are expressed, they are those of the author(s) and not of Radcliffe Medical Media. Radcliffe Cardiology is part of Radcliffe Medical Media, an independent publisher and the Radcliffe Group Ltd. It is not affiliated with or is an agent of, the Oxford Heart Centre, the John Radcliffe Hospital or the Oxford University Hospitals NHS Foundation Trust group.
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