  Artificial intelligence and machine learning are poised to disrupt PET
imaging from bench to clinic. In this perspective we offer insights into how
the technology could be applied to improve the design and synthesis of new
radiopharmaceuticals for PET imaging, including identification of an optimal
labeling approach as well as strategies for radiolabeling reaction
optimization.
