  Spatial transcriptomics (ST) has advanced significantly in the last few
years. Such advancement comes with the urgent need for novel computational
methods to handle the unique challenges of ST data analysis. Many artificial
intelligence (AI) methods have been developed to utilize various machine
learning and deep learning techniques for computational ST analysis. This
review provides a comprehensive and up-to-date survey of current AI methods for
ST analysis.
