<records><record><language>eng</language><publisher>Société de Biomécanique</publisher><journalTitle>Multidisciplinary Biomechanics Journal</journalTitle><eissn>3076-1158</eissn><publicationDate>2025-10-24</publicationDate><volume>50th congress of the Société...</volume><issue>Fluid and biological flows</issue><doi>10.46298/mbj.16176</doi><publisherRecordId>16176</publisherRecordId><documentType>journal article</documentType><title language="eng">Physics-Informed Deep Learning Surrogates for Aneurysm Blood Flow Simulation</title><authors><author><name>Oscar L. Cruz-González</name><affiliationId>0</affiliationId></author><author><name>Valérie Deplano</name></author><author><name>Badih Ghattas</name></author></authors><affiliationsList><affiliationName affiliationId="0">Institut de Recherche sur les Phénomènes Hors Equilibre</affiliationName></affiliationsList><fullTextUrl format="pdf">http://mbj.episciences.org/16176/pdf</fullTextUrl><keywords><keyword>Physics-Informed Neural Networks (PINNs)</keyword><keyword>Deep Operator Networks (DeepONets)</keyword><keyword>Abdominal Aortic Aneurysm (AAA)</keyword><keyword>Computational Fluid Dynamics (CFD)</keyword><keyword>Surrogate Modeling</keyword><keyword>[PHYS.MECA.BIOM]Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph]</keyword></keywords></record></records>