ArticleFrontiers in oncology2021
Personalized Survival Prediction of Patients With Acute Myeloblastic Leukemia Using Gene Expression Profiling.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Identification and validation of immune-associated gene signatures for prognostic prediction in acute myeloid leukemia.Medicine · 2025Article
- Biological Data Resources and Machine Learning Frameworks for Hematology Research.Genomics, proteomics & bioinformatics · 2025Review
- Research advances in the adjunctive diagnosis of acute myeloid leukemia.Frontiers in oncology · 2025Review
- Decoding Acute Myeloid Leukemia: A Clinician's Guide to Functional Profiling.Diagnostics (Basel, Switzerland) · 2024Review
- Stellae-123 gene expression signature improved risk stratification in taiwanese acute myeloid leukemia patients.Scientific reports · 2024Article
- Upregulation of lnc-FOXD2-AS1, CDC45, and CDK1 in patients with primary non-M3 AML is associated with a worse prognosis.Blood research · 2024Article
- mImmunity, inflammation and disease · 2024Article
- A decision support system to recommend appropriate therapy protocol for AML patients.Frontiers in artificial intelligence · 2024Article
- Single-cell multi-omics reveal stage of differentiation and trajectory-dependent immunity-related gene expression patterns in human erythroid cells.Frontiers in immunology · 2024Article
- Diagnosis of acute myeloid leukaemia on microarray gene expression data using categorical gradient boosted trees.Heliyon · 2023Article
- Gene expression profiling unveils the temporal dynamics of CIGB-300-regulated transcriptome in AML cell lines.BMC genomics · 2023Article
- Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia.BMC medical informatics and decision making · 2022Article
- HERVs characterize normal and leukemia stem cells and represent a source of shared epitopes for cancer immunotherapy.American journal of hematology · 2022Article
- Harnessing the power of sphingolipids: Prospects for acute myeloid leukemia.Blood reviews · 2022Review
- Current Status and Perspectives of Allogeneic Hematopoietic Stem Cell Transplantation in Elderly Patients with Acute Myeloid Leukemia.Stem cells translational medicine · 2022Review
- Survival prediction in acute myeloid leukemia using gene expression profiling.BMC medical informatics and decision making · 2022Article
- Evaluation of the Stellae-123 prognostic gene expression signature in acute myeloid leukemia.Frontiers in oncology · 2022Article
- The Cross Marks the Spot: The Emerging Role of JmjC Domain-Containing Proteins in Myeloid Malignancies.Biomolecules · 2021Review
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute Myeloid Leukemia (AML) is a heterogeneous neoplasm characterized by cytogenetic and molecular alterations that drive patient prognosis. Currently established risk stratification guidelines show a moderate predictive accuracy, and newer tools that integrate multiple molecular variables have proven to provide better results. In this report, we aimed to create a new machine learning model of AML survival using gene expression data. We used gene expression data from two publicly available cohorts in order to create and validate a random forest predictor of survival, which we named ST-123. The most important variables in the model were age and the expression of
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Registered trials
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