Deep learning for diagnosis of acute promyelocytic leukemia via recognition of genomically imprinted morphologic features.

ABSTRACT: Acute promyelocytic leukemia (APL) is a subtype of acute myeloid leukemia (AML), classified by a translocation between chromosomes 15 and 17 [t(15;17)], that is considered a true oncologic emergency though appropriate therapy is considered curative. Therapy is often initiated on clinical suspicion, informed by both clinical presentation as well as direct visualization of the peripheral smear. We hypothesized that genomic imprinting of morphologic features learned by deep learning pattern recognition would have greater discriminatory power and consistency compared to humans, thereby facilitating identification of t(15;17) positive APL. By applying both cell-level and patient-level classification linked to t(15;17) PML/RARA ground-truth, we demonstrate that deep learning is capable of distin

SUBMITTER: Sidhom JW 

PROVIDER: S-EPMC8121867 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature