ArticleCancers2021
Artificial Neural Networks Predicted the Overall Survival and Molecular Subtypes of Diffuse Large B-Cell Lymphoma Using a Pancancer Immune-Oncology Panel.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Artificial Intelligence for Risk Stratification in Diffuse Large B-Cell Lymphoma: A Systematic Review of Classification Models and Predictive Performances.Medical sciences (Basel, Switzerland) · 2025Pooled it
- Artificial intelligence for predicting 30-day mortality after emergency laparotomy.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2026Article
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- Bayesian networks as prognostic models in oncology: a systematic review and recommendations for clinical practice.BMJ oncology · 2026Article
- Artificial intelligence-enabled multi-omics biomarkers for immune checkpoint blockade: mechanisms, predictive modeling, and clinical translation.Frontiers in immunology · 2026Review
- Artificial Intelligence-Enabled Multi-Omics for Predicting Immune Checkpoint Inhibitor Response and Resistance.Journal of multidisciplinary healthcare · 2026Review
- Mortality Prediction in Diffuse Large B-Cell Lymphoma Using Supervised Machine Learning Models-A Retrospective Study.Journal of clinical medicine · 2025Article
- MicroRNAs in Diffuse Large B-Cell Lymphoma (DLBCL): Biomarkers with Prognostic Potential.Cancers · 2025Article
- Tumor Biology Hides Novel Therapeutic Approaches to Diffuse Large B-Cell Lymphoma: A Narrative Review.International journal of molecular sciences · 2024Review
- Celiac Disease Deep Learning Image Classification Using Convolutional Neural Networks.Journal of imaging · 2024Article
- Article
- Deep Learning in Hematology: From Molecules to Patients.Clinical hematology international · 2024Review
- Artificial intelligence and classification of mature lymphoid neoplasms.Exploration of targeted anti-tumor therapy · 2024Review
- Construction of disulfidptosis-based immune response prediction model with artificial intelligence and validation of the pivotal grouping oncogene c-MET in regulating T cell exhaustion.Frontiers in immunology · 2024Article
- In silico study of polyphenols as potential inhibitors of MALT1 protein in non-Hodgkin lymphoma.Medical oncology (Northwood, London, England) · 2023Article
- Surface TREM2 on circulating M-MDSCs as a novel prognostic factor for adults with treatment-naïve diffuse large B-cell lymphoma.Experimental hematology & oncology · 2023Article
- Mutational Profile and Pathological Features of a Case of Interleukin-10 and RGS1-Positive Spindle Cell Variant Diffuse Large B-Cell Lymphoma.Hematology reports · 2023Article
- miR-141-3p accelerates ovarian cancer progression and promotes M2-like macrophage polarization by targeting the Keap1-Nrf2 pathway.Open medicine (Warsaw, Poland) · 2023Article
- Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma.Frontiers in molecular biosciences · 2023Article
- Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 4 countries.
Funding
Abstract
Diffuse large B-cell lymphoma (DLBCL) is one of the most frequent subtypes of non-Hodgkin lymphomas. We used artificial neural networks (multilayer perceptron and radial basis function), machine learning, and conventional bioinformatics to predict the overall survival and molecular subtypes of DLBCL. The series included 106 cases and 730 genes of a pancancer immune-oncology panel (nCounter) as predictors. The multilayer perceptron predicted the outcome with high accuracy, with an area under the curve (AUC) of 0.98, and ranked all the genes according to their importance. In a multivariate analysis,
Indexed as
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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.