Publications by the researcher in collaboration with Andrés Peleteiro Raindo (13)
2023
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A prognostic model based on gene expression parameters predicts a better response to bortezomib-containing immunochemotherapy in diffuse large B-cell lymphoma
Frontiers in Oncology, Vol. 13
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Corrigendum: Evaluation of the Stellae-123 prognostic gene expression signature in acute myeloid leukemia(Front. Oncol., (2022), 12, (968340), 10.3389/fonc.2022.968340)
Frontiers in Oncology
2022
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Erratum: Correction: Gene expression profiling identifies FLT3 mutation-like cases in wild-type FLT3 acute myeloid leukemia (PloS one (2021) 16 2 (e0247093))
PloS one
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Evaluation of the Stellae-123 prognostic gene expression signature in acute myeloid leukemia
Frontiers in Oncology, Vol. 12
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Immune Checkpoint Inhibitors in Acute Myeloid Leukemia: A Meta-Analysis
Frontiers in Oncology, Vol. 12
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Prognostic Stratification of Diffuse Large B-cell Lymphoma Using Clinico-genomic Models: Validation and Improvement of the LymForest-25 Model
HemaSphere, Vol. 6, Núm. 4
2021
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Detection of new drivers of frequent B-cell lymphoid neoplasms using an integrated analysis of whole genomes
PloS one, Vol. 16, Núm. 5, pp. e0248886
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Gene expression profiling identifies FLT3 mutation-like cases in wild-type FLT3 acute myeloid leukemia
PloS one, Vol. 16, Núm. 2, pp. e0247093
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Personalized Survival Prediction of Patients With Acute Myeloblastic Leukemia Using Gene Expression Profiling
Frontiers in Oncology, Vol. 11
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Personally Tailored Survival Prediction of Patients With Follicular Lymphoma Using Machine Learning Transcriptome-Based Models
Frontiers in Oncology, Vol. 11
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Safety of FLT3 inhibitors in patients with acute myeloid leukemia
Expert Review of Hematology, Vol. 14, Núm. 9, pp. 851-865
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Survival prediction and treatment optimization of multiple myeloma patients using machine-learning models based on clinical and gene expression data
Leukemia, Vol. 35, Núm. 10, pp. 2924-2935