Taking clinicopathological characteristics and fusion genes (CBFβ::MYH11, RUNX1::RUNX1T1, KMT2A::ELL, and KMT2A::MLLT10) as input variables and OS of non-APL pediatric patients with AML as an output variable, a neural network prediction model is constructed to evaluate the accuracy of risk score prediction for OS. This evidence concerns the gene MLLT10 and acute promyelocytic leukemia.