General schematic showing how deep learning and neural networks are often applied for image processing and single-cell imaging analyses discussed in the main text. Given an input of a high-content image with specific features of interest, a trained neural network can provide an output related to image processing, segmentation/classification of cells, and clustering/neighborhood analysis of cell types found in tissue. Machine learning can also be used for building predictive models (e.g. prediction of drug responses). Numbers in parentheses represent cases in the citing literature in which machine learning was utilized for the specific computational framework. See text for further details. Created with BioRender.com.