Multifidelity deep learning modeling of spatiotemporal lung mechanics
These results demonstrate the potential of the rMFNN lung model to enable patient-specific predictions in acceptable computing times that can be used to personalize mechanical ventilation therapy in critical patients.
Authors
- Daniel E. Hurtado (ORCID: https://orcid.org/0000-0001-6261-9106)
- Javier Yáñez (ORCID: https://orcid.org/0000-0002-1636-1367)
Institutions
- Pontificia Universidad Católica de Chile (CL)
- Massachusetts Institute of Technology (US)
- The University of Texas at Austin (US)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-09-24
- DOI
- https://doi.org/10.3389/fphys.2025.1661418
- Primary Topic
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00