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Showing 10,801 - 10,820 results of 10,960 for search '(((( data processing algorithm ) OR ( based method algorithm ))) OR ( element method algorithm ))', query time: 0.53s Refine Results
  1. 10801
    Image 11_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.tif

    Image 11_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patie... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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  2. 10802
    Image 2_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.tif

    Image 2_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patien... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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  3. 10803
    Data Sheet 1_Integrative multi-omics identifies MEIS3 as a diagnostic biomarker and immune modulator in hypertrophic cardiomyopathy.docx

    Data Sheet 1_Integrative multi-omics identifies MEIS3 as a diagnostic biomarker and immune modulator in hypertrophic cardiomyopathy.docx by Jinchen He (18929662)

    Published 2025
    “…Machine learning algorithms (LASSO and Random Forest) were used to identify key diagnostic genes. …”
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  4. 10804
    Image 4_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.tif

    Image 4_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.tif by Peize Yu (21837977)

    Published 2025
    “…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …”
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  5. 10805
    Image 9_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.tif

    Image 9_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patien... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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  6. 10806
    Table 2_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.xlsx

    Table 2_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patien... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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  7. 10807
    Table 3_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.xlsx

    Table 3_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patien... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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  8. 10808
    Table 1_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.docx

    Table 1_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patien... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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  9. 10809
    Image 12_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.tif

    Image 12_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patie... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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  10. 10810
    Table 2_An explainable machine learning model for predicting preterm birth in pregnant women with gestational diabetes mellitus and hypertensive disorders of pregnancy: development and external validation.xlsx

    Table 2_An explainable machine learning model for predicting preterm birth in pregnant women with gestational diabetes mellitus and hypertensive disorders of pregnancy: development... by Landan Kang (20108214)

    Published 2025
    “…Multiple machine learning algorithms, including Least Absolute Shrinkage and Selection Operator (LASSO) regression, Random Forest (RF), and Naive Bayes (NB), were applied to construct predictive models. …”
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  11. 10811
    Supplementary file 1_The role of α-hydroxybutyrate in modulating sepsis progression: identification of key targets and biomarkers through multi-database data mining, machine learning, and unsupervised clustering.xlsx

    Supplementary file 1_The role of α-hydroxybutyrate in modulating sepsis progression: identification of key targets and biomarkers through multi-database data mining, machine learni... by Qing Lu (28914)

    Published 2025
    “…Functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning algorithms (L1-LASSO, RF, and SVM) were applied to identify biomarkers. …”
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  12. 10812
    Table 1_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.xlsx

    Table 1_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.xlsx by Peize Yu (21837977)

    Published 2025
    “…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …”
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  13. 10813
    Image 3_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.tif

    Image 3_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patien... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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  14. 10814
    Image 2_Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.jpeg

    Image 2_Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.jpeg by Ruoya Wang (842048)

    Published 2025
    “…This study aimed to determine whether polyamine metabolism-related genes (PMRGs) could predict prognosis and immunotherapy efficacy in Breast Cancer (BC).</p>Methods<p>We conducted a comprehensive multi-omics analysis of PMRG expression profiles in BC. …”
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  15. 10815
    Image 1_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.tif

    Image 1_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.tif by Peize Yu (21837977)

    Published 2025
    “…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …”
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  16. 10816
    Table 1_An explainable machine learning model for predicting preterm birth in pregnant women with gestational diabetes mellitus and hypertensive disorders of pregnancy: development and external validation.docx

    Table 1_An explainable machine learning model for predicting preterm birth in pregnant women with gestational diabetes mellitus and hypertensive disorders of pregnancy: development... by Landan Kang (20108214)

    Published 2025
    “…Multiple machine learning algorithms, including Least Absolute Shrinkage and Selection Operator (LASSO) regression, Random Forest (RF), and Naive Bayes (NB), were applied to construct predictive models. …”
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  17. 10817
    Presentation1_Extrachromosomal circular DNAs in prostate adenocarcinoma: global characterizations and a novel prediction model.pdf

    Presentation1_Extrachromosomal circular DNAs in prostate adenocarcinoma: global characterizations and a novel prediction model.pdf by Qingliu He (12528332)

    Published 2024
    “…The immune microenvironment of the risk model was quantified using a variety of immunological algorithms, which also identified its characteristics with regard to immunotherapy, immune response, and immune infiltration.…”
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  18. 10818
    Table 1_Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.xlsx

    Table 1_Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.xlsx by Ruoya Wang (842048)

    Published 2025
    “…This study aimed to determine whether polyamine metabolism-related genes (PMRGs) could predict prognosis and immunotherapy efficacy in Breast Cancer (BC).</p>Methods<p>We conducted a comprehensive multi-omics analysis of PMRG expression profiles in BC. …”
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  19. 10819
    Table 1_Integrative multi-omics analysis identifies a PTM-related immune signature and IRF9 as a driver in ccRCC.docx

    Table 1_Integrative multi-omics analysis identifies a PTM-related immune signature and IRF9 as a driver in ccRCC.docx by Zixiang Li (7014416)

    Published 2025
    “…Post-translational modifications (PTMs) regulate immune signaling and tumor behavior, yet PTM-informed biomarkers for ccRCC remain underexplored.</p>Methods<p>We intersected immune-related genes, PTM-related genes, and differentially expressed genes in TCGA-KIRC to derive candidates and built a prognostic model across TCGA and E-MTAB-1980 using multiple algorithms, selecting a random survival forest-based post-translational modification-related signature (PTMRS) with the best performance. …”
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  20. 10820
    Image 6_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.tif

    Image 6_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patien... by Ran Du (552530)

    Published 2025
    “…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”
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