AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
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Study on the characteristics of carotid wall shear stress in type 2 diabetes patients based on ultrasound vector flow imaging. [PDF]
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Rapid prediction of wall shear stress in stenosed coronary arteries based on deep learning. [PDF]
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Regional aortic wall shear stress increases over time in patients with a bicuspid aortic valve. [PDF]
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Flow Rate and Wall Shear Stress Characterization of a Biomimetic Aerosol Exposure System. [PDF]
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High Wall Shear Stress Is Related to Complicated American Heart Association Lesion Type VI Plaques in Mild-to-Moderate ICA Stenosis: A 3D Cardiovascular MRI Study. [PDF]
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Correction to "Wall Shear Stress Measurements Based on Ultrasound Vector Flow Imaging: Theoretical Studies and Clinical Examples". [PDF]
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