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Showing 1 - 9 results of 9 for search 'multiple bile detection algorithm', query time: 0.25s Refine Results
  1. 1
    Table 2_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx

    Table 2_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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  2. 2
    Table 8_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx

    Table 8_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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  3. 3
    Table 1_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx

    Table 1_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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  4. 4
    Table 4_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx

    Table 4_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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  5. 5
    Table 5_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx

    Table 5_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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  6. 6
    Table 6_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx

    Table 6_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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  7. 7
    Table 7_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx

    Table 7_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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  8. 8
    Table 3_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx

    Table 3_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.xlsx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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  9. 9
    Data Sheet 1_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.docx

    Data Sheet 1_Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.docx by Taorui Wang (22300702)

    Published 2025
    “…Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR), were applied to construct predictive models. …”
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