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Showing 61 - 80 results of 1,030 for search '(( auc values increased ) OR ((( ct values decrease ) OR ( ct largest decrease ))))*', query time: 0.52s Refine Results
  1. 61
    Performance of the 90-day and 1-year mortality prediction models.

    Performance of the 90-day and 1-year mortality prediction models. by Shengtao Li (2018101)

    Published 2024
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  2. 62
    Nomograms for predicting 90-day and 1-year mortality in AKI patients.

    Nomograms for predicting 90-day and 1-year mortality in AKI patients. by Shengtao Li (2018101)

    Published 2024
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  3. 63
    The flow chart of patient’s selection.

    The flow chart of patient’s selection. by Shengtao Li (2018101)

    Published 2024
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  4. 64
    Multivariate logistic regression analysis of 90-day and one-year mortality risk in AKI patients.

    Multivariate logistic regression analysis of 90-day and one-year mortality risk in AKI patients. by Shengtao Li (2018101)

    Published 2024
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  5. 65
    The analysis of AUC values of sphingolipid concentrations of patients with atrial fibrillation (before and 24 h after cryoballoon ablation (CBA) therapy) and control individuals in plasma low-density lipoprotein cholesterol (LDL-C) fraction.

    The analysis of AUC values of sphingolipid concentrations of patients with atrial fibrillation (before and 24 h after cryoballoon ablation (CBA) therapy) and control individuals in... by Patrycja Bielawiec (20826799)

    Published 2025
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  6. 66
    The analysis of AUC values of sphingolipid concentrations of patients with atrial fibrillation (before and 24 h after cryoballoon ablation (CBA) therapy) and control individuals in plasma high-density lipoprotein cholesterol (HDL-C) fraction.

    The analysis of AUC values of sphingolipid concentrations of patients with atrial fibrillation (before and 24 h after cryoballoon ablation (CBA) therapy) and control individuals in... by Patrycja Bielawiec (20826799)

    Published 2025
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  7. 67
    The analysis of AUC values of sphingolipid of patients with atrial fibrillation (before and 24 h after cryoballoon ablation (CBA) therapy) and control individuals concentrations in plasma very low-density lipoprotein cholesterol (VLDL-C) fraction.

    The analysis of AUC values of sphingolipid of patients with atrial fibrillation (before and 24 h after cryoballoon ablation (CBA) therapy) and control individuals concentrations in... by Patrycja Bielawiec (20826799)

    Published 2025
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  8. 68
    Daily number of adverse outcomes (bars) and area under the precision-recall curve (AUC-PRC) per day of the fullPIERS model.

    Daily number of adverse outcomes (bars) and area under the precision-recall curve (AUC-PRC) per day of the fullPIERS model. by Guiyou Yang (10259597)

    Published 2025
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  9. 69
    Daily number of adverse outcomes (bars) and area under the precision-recall curve (AUC-PRC) per day of the PIERS-ML model.

    Daily number of adverse outcomes (bars) and area under the precision-recall curve (AUC-PRC) per day of the PIERS-ML model. by Guiyou Yang (10259597)

    Published 2025
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  10. 70
    Effectiveness of the proposed method to decrease chloroplast contamination.

    Effectiveness of the proposed method to decrease chloroplast contamination. by Gabriela Madrid (11871401)

    Published 2025
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  11. 71
    The SHAP (Shapley Additive exPlanations) values of observed variables.

    The SHAP (Shapley Additive exPlanations) values of observed variables. by Xin Zhang (35492)

    Published 2025
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  12. 72
    Predictive value of LPS for CKD stage of the January 2018 to December 2023 cohort.

    Predictive value of LPS for CKD stage of the January 2018 to December 2023 cohort. by Gui Zhang (4017467)

    Published 2025
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  13. 73
    Static analysis of Yelp and Amazon data sets.

    Static analysis of Yelp and Amazon data sets. by An Tong (15916854)

    Published 2025
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  14. 74
    An illustration is provided here to show the details of the proposed GDFGAT model. The model is divided into four modules.

    An illustration is provided here to show the details of the proposed GDFGAT model. The model is divided into four modules. by An Tong (15916854)

    Published 2025
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  15. 75
    Sichuan telecom fraud dataset static analysis.

    Sichuan telecom fraud dataset static analysis. by An Tong (15916854)

    Published 2025
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  16. 76
    The x-axis represents time, from August 2019 to March 2020, and the y-axis represents the total size of feature statistics of fraudsters or non-fraudsters each month.

    The x-axis represents time, from August 2019 to March 2020, and the y-axis represents the total size of feature statistics of fraudsters or non-fraudsters each month. by An Tong (15916854)

    Published 2025
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  17. 77
    Performance comparison of GDFGAT and baseline on Amazon and Yelp dataset.

    Performance comparison of GDFGAT and baseline on Amazon and Yelp dataset. by An Tong (15916854)

    Published 2025
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  18. 78
    Determination process of feature difference weight.

    Determination process of feature difference weight. by An Tong (15916854)

    Published 2025
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  19. 79
    Performance of GDFGAT with different embedding sizes, layers, and multi-head on the Sichuan dataset.

    Performance of GDFGAT with different embedding sizes, layers, and multi-head on the Sichuan dataset. by An Tong (15916854)

    Published 2025
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  20. 80
    Performance comparison of GDFGAT and baseline on SiChuan dataset.

    Performance comparison of GDFGAT and baseline on SiChuan dataset. by An Tong (15916854)

    Published 2025
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