Article Versions Notes

Rowley SD, Gunning TS, Pelliccia M, Della Pia A, Lee A, Behrmann J, Bangolo A, Jandir P, Zhang H, Kaur S, et al. Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation. Cancers. 2024; 16(7):1357. https://doi.org/10.3390/cancers16071357

Rowley, Scott D., Thomas S. Gunning, Michael Pelliccia, Alexandra Della Pia, Albert Lee, James Behrmann, Ayrton Bangolo, Parul Jandir, Hong Zhang, Sukhdeep Kaur, and et al. 2024. "Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation" Cancers 16, no. 7: 1357. https://doi.org/10.3390/cancers16071357

Rowley, S. D., Gunning, T. S., Pelliccia, M., Della Pia, A., Lee, A., Behrmann, J., Bangolo, A., Jandir, P., Zhang, H., Kaur, S., Suh, H. C., Donato, M., Albitar, M., & Ip, A. (2024). Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation. Cancers, 16(7), 1357. https://doi.org/10.3390/cancers16071357