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Computational measurable residual disease assessment in acute myeloid leukemia: a retrospective validation in the HOVON-SAKK-132 trial
Mocking, T. R., Haaksma, L. H., Reuvekamp, T., Kelder, A., Scholten, W. J., Ngai, L. L., Breems, D. A., Fischer, T., Gjertsen, B. T., Griškevičius, L., Juliusson, G., Maertens, J. A., Manz, M. G., Pabst, T., Passweg, J. R., Porkka, K., Valk, P. J. M., Gradowska, P., Löwenberg, B. & de Leeuw, D. C. & 5 others, , 13 Sept 2025, (E-pub ahead of print) In: Leukemia.Research output: Contribution to journal › Article › Academic › peer-review
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Applications of machine learning for immunophenotypic measurable residual disease assessment in acute myeloid leukemia
Mocking, T. R., van de Loosdrecht, A. A., Cloos, J. & Bachas, C., 21 May 2025, In: HemaSphere. 9, 5, 8 p., e70138.Research output: Contribution to journal › Review article › Academic › peer-review
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CD34+CD38- leukemia stem cells predict clinical outcomes in acute myeloid leukemia patients treated non-intensively with hypomethylating agents: ACUTE MYELOID LEUKEMIA
Reuvekamp, T., Ngai, L. L., den Hartog, D., Carbaat-Ham, J., Fayed, M. M. H. E., Scholten, W. J., Mocking, T. R., Chitu, D. A., Pabst, T., Klein, S. K., Stussi, G., Griskevicius, L., Breems, D., van Lammeren-Venema, D., Boersma, R., Ossenkoppele, G. J., van de Loosdrecht, A. A., Bachas, C., Huls, G. A. & de Leeuw, D. C. & 1 others, , Apr 2025, In: Leukemia. 39, 4, p. 972-975 4 p.Research output: Contribution to journal › Article › Academic › peer-review
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