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Showing results for maria donors Barό
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Prediction of Hematopoietic Stem Cell Transplantation Related Mortality- Lessons Learned from the In-Silico Approach: A European Society for Blood and Marrow Transplantation Acute Leukemia Working Party Data Mining Study.
Shouval R, Labopin M, Unger R, Giebel S, Ciceri F, Schmid C, Esteve J, Baron F, Gorin NC, Savani B, Shimoni A, Mohty M, Nagler A. Shouval R, et al. PLoS One. 2016 Mar 4;11(3):e0150637. doi: 10.1371/journal.pone.0150637. eCollection 2016. PLoS One. 2016. PMID: 26942424 Free PMC article.
The top 3 ranking variables, shared by all algorithms were disease stage, donor type, and conditioning regimen. Our findings empirically demonstrate that with regards to NRM prediction, few variables "carry the weight" and that traditional HSCT data has been "worn out". .. …
The top 3 ranking variables, shared by all algorithms were disease stage, donor type, and conditioning regimen. Our findings empirica …
Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study.
Shouval R, Labopin M, Bondi O, Mishan-Shamay H, Shimoni A, Ciceri F, Esteve J, Giebel S, Gorin NC, Schmid C, Polge E, Aljurf M, Kroger N, Craddock C, Bacigalupo A, Cornelissen JJ, Baron F, Unger R, Nagler A, Mohty M. Shouval R, et al. J Clin Oncol. 2015 Oct 1;33(28):3144-51. doi: 10.1200/JCO.2014.59.1339. Epub 2015 Aug 3. J Clin Oncol. 2015. PMID: 26240227 Free article.
Secondary objectives were estimation of nonrelapse mortality, leukemia-free survival, and overall survival at 2 years. Donor, recipient, and procedural characteristics were analyzed. The alternating decision tree machine learning algorithm was applied for model development …
Secondary objectives were estimation of nonrelapse mortality, leukemia-free survival, and overall survival at 2 years. Donor, recipie …