AIMC Topic: Leukemia, Myeloid, Acute
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A 29-gene and cytogenetic score for the prediction of resistance to induction treatment in acute myeloid leukemia.
Haematologica
Dec 14, 2017
Primary therapy resistance is a major problem in acute myeloid leukemia treatment. We set out to develop a powerful and robust predictor for therapy resistance for intensively treated adult patients. We used two large gene expression data sets (n=856...
The mutational oncoprint of recurrent cytogenetic abnormalities in adult patients with de novo acute myeloid leukemia.
Leukemia
Mar 24, 2017
Recurrent chromosomal abnormalities and gene mutations detected at the time of diagnosis of acute myeloid leukemia (AML) are associated with particular disease features, treatment response and survival of AML patients, and are used to denote specific...
Peripheral FLT-3 ligand levels as a pathobiological parameter duringthe clinical course of acute myeloid leukemia.
Turkish journal of medical sciences
Dec 20, 2016
BACKGROUND/AIM: FLT-3 ligand is a growth factor affecting the hematopoietic lineage. The aim of this study was to evaluate the variability of peripheral FLT-3 ligand during the clinical course of acute myeloid leukemia (AML) patients.
Consistent quantitative gene product expression: #3. Invariance with age.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Oct 18, 2016
The quantitative expression of cell surface antigens and light scattering properties of five cellular reference populations in stressed bone marrow specimens were compared between pediatric and adult patients treated for acute myeloid leukemia (AML)....
Consistent quantitative gene product expression: #2. Antigen intensities on bone marrow cells are invariant between individuals.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Oct 18, 2016
Five reference populations in bone marrow specimens were identified by flow cytometry using specific combinations of reagents in order define the variation of gene product expression intensities both within and between individuals. Mature lymphocytes...
Consistent quantitative gene product expression: #1. Automated identification of regenerating bone marrow cell populations using support vector machines.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Jul 14, 2016
Identification and quantification of maturing hematopoietic cell populations in flow cytometry data sets is a complex and sometimes irreproducible step in data analysis. Supervised machine learning algorithms present promise to automatically classify...
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.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Aug 3, 2015
PURPOSE: Allogeneic hematopoietic stem-cell transplantation (HSCT) is potentially curative for acute leukemia (AL), but carries considerable risk. Machine learning algorithms, which are part of the data mining (DM) approach, may serve for transplanta...
Treatment Outcome
Europe
Decision Trees
Predictive Value of Tests
Area Under Curve
Registries
Disease-Free Survival
Data Mining
Disease Progression
Time Factors
ROC Curve
Logistic Models
Humans
Middle Aged
Machine Learning
Risk Assessment
Algorithms
Postoperative Complications
Hematopoietic Stem Cell Transplantation
Risk Factors
Decision Support Techniques
Transplantation, Homologous
Adult
Retrospective Studies
Precursor Cell Lymphoblastic Leukemia-Lymphoma
Leukemia, Myeloid, Acute
Female
Kaplan-Meier Estimate
Male
Reproducibility of Results
Integrating GO and KEGG terms to characterize and predict acute myeloid leukemia-related genes.
Hematology (Amsterdam, Netherlands)
Oct 24, 2014
BACKGROUND/OBJECTIVE: Acute myeloid leukemia (AML) is a progressive and malignant cancer of myelogenous blood cells, which disturbs the production of normal blood cells. Although several risk and genetic factors (AML-related genes) have been investig...
A Machine Learning-Based Strategy Predicts Selective and Synergistic Drug Combinations for Relapsed Acute Myeloid Leukemia.
Cancer research
Jul 15, 2025
UNLABELLED: Combination therapies are one potential approach to improve the outcomes of patients with relapsed/refractory (R/R) disease. However, comprehensive testing in scarce primary patient material is hampered by the many drug combination possib...
A machine learning framework for cross-institute standardized analysis of flow cytometry in differentiating acute myeloid leukemia from non-neoplastic conditions.
Computers in biology and medicine
Jul 1, 2025
Flow cytometry (FC) remains a cornerstone diagnostic tool for acute myeloid leukemia (AML), yet standardizing panels across laboratories presents persistent challenges. Our study introduces a validated machine learning framework enabling cross-panel ...
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