168605 20260211123813.0 doi 10.1016/j.compbiomed.2026.111472 sideral 148037 ART-2026-148037 eng Orera, J. Universidad de Zaragoza Reconstructing in-vitro and in-vivo signals and parameters in networks of elastic vessels using physics-informed neural networks 2026 The reconstruction of waveforms and hidden parameters is crucial for the physical modeling of steady and transient flows in networks of elastic vessels (arteries), where many mechanical properties are not directly measurable. This work investigates the potential of Physics-Informed Neural Networks (PINNs) to address the challenge of reconstructing pressure and flow signals and inferring parameters from experimental data. We incorporate the zero-dimensional (0D) system of coupled differential equations that describe flow in elastic vessels into the neural network, which we call 0D-PINN. We evaluate our methodology with several test cases representing different dynamical systems, including an experimental mock arterial network with 37 silicone vessels replicating the human arterial system, as well as a clinical case based on in-vivo MRI data from a healthy adult’s thoracic aorta. It is shown that coupling 0D models with Physics-Informed Neural Networks (PINNs) enables the recovery of parameters and waveforms from experimental in-vitro or in-vivo data. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/ES/AEI/PID2023-150074NB-I00 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Mairal, J. Universidad de Zaragoza (orcid)0000-0001-7056-6913 Sánchez-Fuster, L. Universidad de Zaragoza Murillo, J. Universidad de Zaragoza (orcid)0000-0002-1386-5543 5001 600 Universidad de Zaragoza Dpto. Ciencia Tecnol.Mater.Fl. Área Mecánica de Fluidos 203 (2026), 111472 [19 pp.] Comput. biol. med. Computers in biology and medicine 0010-4825 10023144 http://zaguan.unizar.es/record/168605/files/texto_completo.pdf Versión publicada 2304136 http://zaguan.unizar.es/record/168605/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:168605 articulos driver 2026-02-11-10:28:07 ARTICLE