Imaging-based phenotypic screening of cell-based disease models has become an indispensable tool for modern drug discovery. Despite the growing adoption of high-content screening (HCS), analyzing the complex imaging data produced by these systems is particularly time-consuming.

However, recent advances in deep learning have enabled the possibility of automating these analyses.

Download this poster to discover a workflow for successful automation of HCS, with details surrounding:

• How to analyze multiple datasets with minimal tuning
• The deep learning algorithms used
• A case study using the automated workflow