Search alternatives:
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search), we decrease (Expand Search)
nn decrease » _ decrease (Expand Search), gy decreased (Expand Search), b1 decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
2 step » _ step (Expand Search), a step (Expand Search)
Showing 9,081 - 9,100 results of 30,932 for search '(( 2 step decrease ) OR ( 50 ((((mean decrease) OR (nn decrease))) OR (a decrease)) ))', query time: 1.29s Refine Results
  1. 9081
    Maintenance of weight loss or stability in subjects with obesity: a retrospective longitudinal analysis of a real-world population

    Maintenance of weight loss or stability in subjects with obesity: a retrospective longitudinal analysis of a real-world population by Maral DerSarkissian (504144)

    Published 2018
    “…</p> <p><b>Methods:</b> A retrospective observational longitudinal study of subjects with obesity was conducted using the General Electric Centricity electronic medical record database. …”
    Save to List
    Saved in:
  2. 9082
    IG feature selection process.

    IG feature selection process. by Ahmed Muqdad Alnasrallah (21647492)

    Published 2025
    “…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”
    Save to List
    Saved in:
  3. 9083
    RFE feature selection process.

    RFE feature selection process. by Ahmed Muqdad Alnasrallah (21647492)

    Published 2025
    “…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”
    Save to List
    Saved in:
  4. 9084
    CICID2017 dataset information.

    CICID2017 dataset information. by Ahmed Muqdad Alnasrallah (21647492)

    Published 2025
    “…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”
    Save to List
    Saved in:
  5. 9085
    Shows the basic architecture of an autoencoder.

    Shows the basic architecture of an autoencoder. by Ahmed Muqdad Alnasrallah (21647492)

    Published 2025
    “…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”
    Save to List
    Saved in:
  6. 9086
    Architecture of deep neural networks.

    Architecture of deep neural networks. by Ahmed Muqdad Alnasrallah (21647492)

    Published 2025
    “…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”
    Save to List
    Saved in:
  7. 9087
    Proposed model framework.

    Proposed model framework. by Ahmed Muqdad Alnasrallah (21647492)

    Published 2025
    “…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”
    Save to List
    Saved in:
  8. 9088
    WUSTL-EHMS-2020 dataset information.

    WUSTL-EHMS-2020 dataset information. by Ahmed Muqdad Alnasrallah (21647492)

    Published 2025
    “…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”
    Save to List
    Saved in:
  9. 9089
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  10. 9090
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  11. 9091
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  12. 9092
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  13. 9093
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  14. 9094
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  15. 9095
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  16. 9096
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  17. 9097
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  18. 9098
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  19. 9099
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:
  20. 9100
    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer

    Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer by Xiaoming Chen (230202)

    Published 2024
    “…XZB108, selectively inhibited HDAC8 (IC<sub>50</sub> = 0.90 ± 0.014 μM), suggesting that it may be a promising nonhydroxamate HDAC8 inhibitor. …”
    Save to List
    Saved in:

Search Tools: