Results 211 to 220 of about 400,118 (290)
Blinatumomab-Related Lineage Switch of KMT2A/AFF1-Rearranged B-Lymphoblastic Leukemia to B/Myeloid Mixed-Phenotype Acute Leukemia and Myeloid Sarcoma Causing Spinal Cord Compression. [PDF]
Fan X +5 more
europepmc +1 more source
ABSTRACT This study aimed to explore the differences of peripheral blood (PB) and bone marrow serum lipidomic profiles in severe aplastic anemia (SAA) patients and their significance in predicting earlier immunosuppressive therapy (IST) response. A cohort of 11 newly diagnosed SAA patients and 15 healthy controls were enrolled between June 2020 and ...
Zexing Sun +11 more
wiley +1 more source
Data‐Independent Acquisition Mass Spectrometry in Tumor Classification and Cancer Biomarker Research
Abstract Cancer treatment is far from optimal also because current classification systems do not reflect the complex molecular status of the tumor and its phenotype in sufficient detail. To construct molecular tumor classifiers, omics tools provide complex molecular data reflecting many aspects from genotype to phenotype.
Jan Simonik +3 more
wiley +1 more source
Clinical Outcomes of Adult Patients With Newly Diagnosed Mixed Phenotype Acute Leukemia. [PDF]
Goulart H +27 more
europepmc +1 more source
Improved survival after acute graft-versus-host disease diagnosis in the modern era [PDF]
et al.,, Hayashi, Robert J, Vig, Ravi
core +1 more source
Using data from the Global Burden of Disease Study 2021, we systematically assessed leukemia prevalence and disability‐adjusted life years (DALYs) across 204 countries and territories from 1990 to 2021, stratified by subtype, demographics, and risk factors.
Yuping Wu +8 more
wiley +1 more source
Comparison of changes in blood cells and hemostatic biomarkers in mouse xenograft models of acute myeloid leukemia and acute promyelocytic leukemia. [PDF]
Archibald SJ +5 more
europepmc +1 more source
Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu +3 more
wiley +1 more source

