Detalhe da pesquisa
1.
Predictors of unsustained measurable residual disease negativity in transplant-eligible patients with multiple myeloma.
Blood
; 143(7): 597-603, 2024 Feb 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-38048552
2.
Improved personalized survival prediction of patients with diffuse large B-cell Lymphoma using gene expression profiling.
BMC Cancer
; 20(1): 1017, 2020 Oct 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-33087075
3.
Refining risk prediction in pediatric acute lymphoblastic leukemia through DNA methylation profiling.
Clin Epigenetics
; 16(1): 49, 2024 03 28.
Artigo
em Inglês
| MEDLINE | ID: mdl-38549146
4.
Corrigendum: Evaluation of the Stellae-123 prognostic gene expression signature in acute myeloid leukemia.
Front Oncol
; 13: 1302993, 2023.
Artigo
em Inglês
| MEDLINE | ID: mdl-37860185
5.
A prognostic model based on gene expression parameters predicts a better response to bortezomib-containing immunochemotherapy in diffuse large B-cell lymphoma.
Front Oncol
; 13: 1157646, 2023.
Artigo
em Inglês
| MEDLINE | ID: mdl-37188190
6.
Prognostic Stratification of Multiple Myeloma Using Clinicogenomic Models: Validation and Performance Analysis of the IAC-50 Model.
Hemasphere
; 6(8): e760, 2022 Aug.
Artigo
em Inglês
| MEDLINE | ID: mdl-35935610
7.
A Machine Learning Model Based on Tumor and Immune Biomarkers to Predict Undetectable MRD and Survival Outcomes in Multiple Myeloma.
Clin Cancer Res
; 28(12): 2598-2609, 2022 06 13.
Artigo
em Inglês
| MEDLINE | ID: mdl-35063966
8.
Evaluation of the Stellae-123 prognostic gene expression signature in acute myeloid leukemia.
Front Oncol
; 12: 968340, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-36059646
9.
Prognostic Stratification of Diffuse Large B-cell Lymphoma Using Clinico-genomic Models: Validation and Improvement of the LymForest-25 Model.
Hemasphere
; 6(4): e706, 2022 Apr.
Artigo
em Inglês
| MEDLINE | ID: mdl-35392483
10.
Unsupervised machine learning improves risk stratification in newly diagnosed multiple myeloma: an analysis of the Spanish Myeloma Group.
Blood Cancer J
; 12(4): 76, 2022 04 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-35468898
11.
Survival prediction and treatment optimization of multiple myeloma patients using machine-learning models based on clinical and gene expression data.
Leukemia
; 35(10): 2924-2935, 2021 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-34007046
12.
Personalized Survival Prediction of Patients With Acute Myeloblastic Leukemia Using Gene Expression Profiling.
Front Oncol
; 11: 657191, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-33854980
13.
Personally Tailored Survival Prediction of Patients With Follicular Lymphoma Using Machine Learning Transcriptome-Based Models.
Front Oncol
; 11: 705010, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-35083135
14.
Detection of new drivers of frequent B-cell lymphoid neoplasms using an integrated analysis of whole genomes.
PLoS One
; 16(5): e0248886, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-33945543
15.
Detection of Rare Germline Variants in the Genomes of Patients with B-Cell Neoplasms.
Cancers (Basel)
; 13(6)2021 Mar 16.
Artigo
em Inglês
| MEDLINE | ID: mdl-33809641
16.
Gene expression profiling identifies FLT3 mutation-like cases in wild-type FLT3 acute myeloid leukemia.
PLoS One
; 16(2): e0247093, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-33592069
17.
Novel Mutation Hotspots within Non-Coding Regulatory Regions of the Chronic Lymphocytic Leukemia Genome.
Sci Rep
; 10(1): 2407, 2020 02 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-32051441
18.
New Recurrent Structural Aberrations in the Genome of Chronic Lymphocytic Leukemia Based on Exome-Sequencing Data.
Front Genet
; 10: 854, 2019.
Artigo
em Inglês
| MEDLINE | ID: mdl-31616467
19.
Time to Treatment Prediction in Chronic Lymphocytic Leukemia Based on New Transcriptional Patterns.
Front Oncol
; 9: 79, 2019.
Artigo
em Inglês
| MEDLINE | ID: mdl-30828568
20.
Aspergillus Fumigatus Empyema. / Empiema por Aspergillus fumigatus.
Arch Bronconeumol
; 53(7): 399-400, 2017 Jul.
Artigo
em Inglês, Espanhol
| MEDLINE | ID: mdl-28024667