Abstract
A machine learning analysis was employed to predict the expression of key chromosomal alterations and the cytogenetic risk of multiple myeloma patients. The proposed machine learning analysis based on sacrum and pelvis radiomics achieved the highest performance with an AUC of 0.76±0.03 among other radiocytogenetic models.