Imagingomics transforms traditional medical images into mineable high-throughput image features for quantitatively describing spatial-temporal heterogeneity in images and revealing image features that cannot be recognized by the naked eye. It can effectively convert medical images into a high-dimensional recognizable feature space and statistically analyze the generated feature space to build models with diagnostic, prognostic, or predictive value. It is more of an aid than a decider.