Machine learning-guided morphological property prediction of 2D electrospun scaffolds: the effect of polymer chemical composition and processing parameters

Abstract

ML was adopted to predict electrospun scaffolds' morphological properties. The scaffolds' conductivity and fiber diameter were modeled by machine learning. A deep neural network model showed a prediction accuracy with an R2 score of more than 0.7.