ArticleCancer gene therapy2020
Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine.
Article in Cancer gene therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
33 citing papers in PubMed.
- Machine Learning in Stem Cell Research: From Biological Data to Clinical Translation.Computational and structural biotechnology journal · 2026Review
- Interpretable machine learning model for predicting recurrence in patients with diabetic foot ulcers.BMJ open diabetes research & care · 2025Article
- Application of image recognition technology in pathological diagnosis of blood smears.Clinical and experimental medicine · 2024Review
- A literature review: machine learning-based stem cell investigation.Annals of translational medicine · 2024Review
- Optimization of diagnosis and treatment of hematological diseases via artificial intelligence.Frontiers in medicine · 2024Review
- Cuffless Hypertension Detection using Swarm Support Vector Machine Utilizing Photoplethysmogram and Electrocardiogram.Journal of biomedical physics & engineering · 2023Article
- IGFBP5 is an ROR1 ligand promoting glioblastoma invasion via ROR1/HER2-CREB signaling axis.Nature communications · 2023Article
- Identification of Smoking-Associated Transcriptome Aberration in Blood with Machine Learning Methods.BioMed research international · 2023Article
- Identification of genes related to immune enhancement caused by heterologous ChAdOx1-BNT162b2 vaccines in lymphocytes at single-cell resolution with machine learning methods.Frontiers in immunology · 2023Article
- Characterization of chromatin accessibility patterns in different mouse cell types using machine learning methods at single-cell resolution.Frontiers in genetics · 2023Article
- Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method.Life (Basel, Switzerland) · 2022Article
- Multimetric feature selection for analyzing multicategory outcomes of colorectal cancer: random forest and multinomial logistic regression models.Laboratory investigation; a journal of technical methods and pathology · 2022Article
- Cancer gene therapy 2020: highlights from a challenging year.Cancer gene therapy · 2022Article
- Identifying anal and cervical tumorigenesis-associated methylation signaling with machine learning methods.Frontiers in oncology · 2022Article
- Identification of cortical interneuron cell markers in mouse embryos based on machine learning analysis of single-cell transcriptomics.Frontiers in neuroscience · 2022Article
- A regulatory miRNA-mRNA network is associated with transplantation response in acute kidney injury.Human genomics · 2021Article
- Taming Cell-to-Cell Heterogeneity in Acute Myeloid Leukaemia With Machine Learning.Frontiers in oncology · 2021Review
- Identifying COVID-19-Specific Transcriptomic Biomarkers with Machine Learning Methods.BioMed research international · 2021Article
- Application of machine learning in the management of acute myeloid leukemia: current practice and future prospects.Blood advances · 2020Review
- Identification of Gene Signatures and Expression Patterns During Epithelial-to-Mesenchymal Transition From Single-Cell Expression Atlas.Frontiers in genetics · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute myeloid leukemia (AML) is a type of blood cancer characterized by the rapid growth of immature white blood cells from the bone marrow. Therapy resistance resulting from the persistence of leukemia stem cells (LSCs) are found in numerous patients. Comparative transcriptome studies have been previously conducted to analyze differentially expressed genes between LSC
Indexed as
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.