The development of prognostic and predictive biomarkers for oncology patients remains an important challenge, which in recent years has been accelerated by advancements in diverse fields including the derivation of advanced imaging features from modalities such as computed tomography (CT) [1], new laboratory science including the detection of circulating tumor deoxyribonucleic acid (ctDNA) [2], and, of course, the rise of artificial intelligence (AI) [3].