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Showing 1 - 15 results of 15 for search '(((("i values decrease") OR ("auc values increased"))) OR ("b large decrease"))', query time: 0.55s Refine Results
  1. 1
    Proportion of Feature Importance.

    Proportion of Feature Importance. by Chunliang Jiang (22477803)

    Published 2025
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  2. 2
    Identification results of four algorithms on test sets for different feature subsets.

    Identification results of four algorithms on test sets for different feature subsets. by Chunliang Jiang (22477803)

    Published 2025
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  3. 3
    Definitions of mortality prediction for patients with hypothermia.

    Definitions of mortality prediction for patients with hypothermia. by Chunliang Jiang (22477803)

    Published 2025
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  4. 4
    Trends for average AUC for (A) different prediction window and (B) different observation window for each model.

    Trends for average AUC for (A) different prediction window and (B) different observation window for each model. by Chunliang Jiang (22477803)

    Published 2025
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  5. 5
    Metrics used to evaluate the prediction performance.

    Metrics used to evaluate the prediction performance. by Chunliang Jiang (22477803)

    Published 2025
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  6. 6
    Feature selection results for (A) Random Forest, (B) Logistic Regression, (C) XGBoost, and (D) Naïve Bayes.

    Feature selection results for (A) Random Forest, (B) Logistic Regression, (C) XGBoost, and (D) Naïve Bayes. by Chunliang Jiang (22477803)

    Published 2025
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  7. 7
    Baseline characteristics of included patients.

    Baseline characteristics of included patients. by Chunliang Jiang (22477803)

    Published 2025
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  8. 8
    Partitioning into training and testing sets.

    Partitioning into training and testing sets. by Chunliang Jiang (22477803)

    Published 2025
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  9. 9
    Process for selection of the study cohort.

    Process for selection of the study cohort. by Chunliang Jiang (22477803)

    Published 2025
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  10. 10
    Appendix DATA: Patient dataset.

    Appendix DATA: Patient dataset. by Chunliang Jiang (22477803)

    Published 2025
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  11. 11
    Trends in AUC values for different observation windows and prediction windows for (A) Random Forest, (B) Logistic Regression, (C) XGBoost, and (D) Naïve Bayes four machine learning methods.

    Trends in AUC values for different observation windows and prediction windows for (A) Random Forest, (B) Logistic Regression, (C) XGBoost, and (D) Naïve Bayes four machine learning... by Chunliang Jiang (22477803)

    Published 2025
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  12. 12
    Non-invasive physiological parameters included in the study.

    Non-invasive physiological parameters included in the study. by Chunliang Jiang (22477803)

    Published 2025
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  13. 13
    Overall process of mortality prediction in patients with hypothermia.

    Overall process of mortality prediction in patients with hypothermia. by Chunliang Jiang (22477803)

    Published 2025
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  14. 14
    Figure 2 from mTORC1-Driven Protein Translation Correlates with Clinical Benefit of Capivasertib within a Genetically Preselected Cohort of <i>PIK3CA</i>-Altered Tumors

    Figure 2 from mTORC1-Driven Protein Translation Correlates with Clinical Benefit of Capivasertib within a Genetically Preselected Cohort of <i>PIK3CA</i>-Altered Tumors by Constance A. Sobsey (19373550)

    Published 2025
    “…Node size increases as the <i>P</i>-value decreases. <b>B,</b> Top 20 canonical pathways that are significantly differentially activated between clinical benefit (CB) and no clinical benefit (NCB) groups, based on assessment with Fisher’s exact test in Qiagen IPA. …”
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  15. 15
    Data Sheet 1_The triglyceride glucose-body mass index predicts adverse reproductive outcomes in women with polycystic ovary syndrome undergoing frozen embryo transfer.docx

    Data Sheet 1_The triglyceride glucose-body mass index predicts adverse reproductive outcomes in women with polycystic ovary syndrome undergoing frozen embryo transfer.docx by Ziyin Ding (16557384)

    Published 2025
    “…Combined with other identified risk factors, including basal luteinizing hormone, basal follicle stimulating hormone, total cholesterol, testosterone, infertility type and controlled ovarian stimulation protocols, the AUC value increased (AUC = 0.667, P < 0.001) and this model showed good miscarriage prediction performance in most subgroups (AUC > 0.650, P < 0.05), especially in patients with normal or low weight (BMI < 24 kg/m<sup>2</sup>, AUC = 0.743, P < 0.001).…”
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