Machine Learning Enhancement of Flow Cytometry Data Accelerates the Identification of Minimal Residual Acute Myeloid Leukemia

MLA

Seheult, Jansen N., et al. “Machine Learning Enhancement of Flow Cytometry Data Accelerates the Identification of Minimal Residual Acute Myeloid Leukemia.” Blood, vol. 142, no. 1, Number 1 Supplement 1, Nov. 2023, p. 4339. EBSCOhost, https://doi.org/10.1182/blood-2023-190275.

APA

Seheult, J. N., Shi, M., Olteanu, H., Otteson, G. E., Timm, M. M., Weybright, M. J., & Horna, P. (2023). Machine Learning Enhancement of Flow Cytometry Data Accelerates the Identification of Minimal Residual Acute Myeloid Leukemia. Blood, 142(1, Number 1 Supplement 1), 4339. https://doi.org/10.1182/blood-2023-190275

Chicago

Seheult, Jansen N, Min Shi, Horatiu Olteanu, Gregory E Otteson, Michael M Timm, Matthew J Weybright, and Pedro Horna. 2023. “Machine Learning Enhancement of Flow Cytometry Data Accelerates the Identification of Minimal Residual Acute Myeloid Leukemia.” Blood 142 (1, Number 1 Supplement 1): 4339. doi:10.1182/blood-2023-190275.