APA (7th ed.) Citation

Al-Riyami, A., Kadauke, S., Hanna, R., Azar, A. P., Maryamchik, E., Zheng, X., . . . Wang, Y. (2022). 403 - Hematopoietic Stem/Progenitor Cells and Engineering: A MACHINE LEARNING MODEL THAT INCORPORATES CD45 MEAN FLUORESCENCE INTENSITY (MFI) AND CELL COMPOSITION PREDICTS POOR VIABILITY OF HEMATOPOIETIC PROGENITOR CELLS AFTER FREEZE-THAW. Cytotherapy (Elsevier Inc.), 24(5), S99. https://doi.org/10.1016/S1465-3249(22)00284-5

Chicago Style (17th ed.) Citation

Al-Riyami, A.Z, et al. "403 - Hematopoietic Stem/Progenitor Cells and Engineering: A MACHINE LEARNING MODEL THAT INCORPORATES CD45 MEAN FLUORESCENCE INTENSITY (MFI) AND CELL COMPOSITION PREDICTS POOR VIABILITY OF HEMATOPOIETIC PROGENITOR CELLS AFTER FREEZE-THAW." Cytotherapy (Elsevier Inc.) 24, no. 5 (2022): S99. https://doi.org/10.1016/S1465-3249(22)00284-5.

MLA (9th ed.) Citation

Al-Riyami, A.Z, et al. "403 - Hematopoietic Stem/Progenitor Cells and Engineering: A MACHINE LEARNING MODEL THAT INCORPORATES CD45 MEAN FLUORESCENCE INTENSITY (MFI) AND CELL COMPOSITION PREDICTS POOR VIABILITY OF HEMATOPOIETIC PROGENITOR CELLS AFTER FREEZE-THAW." Cytotherapy (Elsevier Inc.), vol. 24, no. 5, 2022, p. S99, https://doi.org/10.1016/S1465-3249(22)00284-5.