arXiv Machine Learning August 17, 2026 By Oscar L. Cruz-Gonzalez, Val\'erie Deplano, Badih Ghattas

Learning Unsteady Aneurysm Hemodynamics with Physics-Informed DeepONets

Read the original on arXiv Machine Learning →

arXiv:2608. 13629v1 Announce Type: cross Abstract: Clinically actionable, patient-specific hemodynamic assessment, specifically wall shear stress, vortex structure and pressure distributions, is critical for determining risky or unfavorable evolution in Abdominal Aortic Aneurysms (AAA).

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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arXiv Machine Learning

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