Physics-Informed Neural Networks can accurately model cardiac electrophysiology in 3D geometries and fibrillatory conditions

Documenti analoghi

• Characterisation of Anti-Arrhythmic Drug Effects on Cardiac Electrophysiology using Physics-Informed Neural Networks
  di: Chiu, Ching-En, et al.
  Pubblicazione: (2024)
• PINNing Cerebral Blood Flow: Analysis of Perfusion MRI in Infants using Physics-Informed Neural Networks
  di: Galazis, Christoforos, et al.
  Pubblicazione: (2024)
• osl-ephys: A Python toolbox for the analysis of electrophysiology data
  di: van Es, Mats W. J., et al.
  Pubblicazione: (2024)
• Continuation methods as a tool for parameter inference in electrophysiology modeling
  di: Owen, Matt J, et al.
  Pubblicazione: (2025)
• MP-GCAN: a highly accurate classifier for $α$-helical membrane proteins and $β$-barrel proteins
  di: Li, Kunyang, et al.
  Pubblicazione: (2025)