Deep Learning-Based System for the Research of Pluripotent Stem Cell-derived Cells

Abstract

Deep learning technology is rapidly advancing, and is now used to solve complex problems. induced pluripotent stem cells (iPSCs) can be used for several purposes such as regenerative medicine, disease modeling study and drug screening. It is inevitable to identify iPSC-derived differentiated cells in microscopy for any use. Here, we used deep learning to establish an automated method to identify endothelial cells derived from iPSCs, without the need for immunostaining or lineage tracing.