Rapid prediction of organisation in engineered corneal, glial and fibroblast tissues using machine learning and biophysical models

We present a machine learning approach for predicting the organisation of corneal, glial and fibroblast cells in 3D cultures used for tissue engineering. Our machine-learning-based method uses a generative adversarial network architecture called pix2pix, which we train using results from biophysical