Clinical Evaluation of the Utility of Machine Learning-Based Subtype Classifiers of Acute Lymphoblastic Leukemia in Identifying Cryptic and Novel Fusions.
Background B-acute lymphoblastic leukemia (B-ALL) is a heterogeneous disease comprising more than 20 molecular subtypes defined by distinct gene expression profiles (GEPs) and genetic alterations. Subtypes primarily defined by GEPs remain challenging to identify using conventional cytogenetic and targeted molecular ass...