Physics-Informed Neural Networks for Biological $2\mathrm{D}{+}t$ Reaction-Diffusion Systems

Summary

This paper extends physics-informed neural networks (PINNs) to discover reaction-diffusion equations from 2D spatial + time data. The method combines neural networks with known physics structure to learn unknown biological processes, demonstrated on lung cancer cell dynamics from microscopy images, producing interpretable mathematical equations.