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)
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)
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15001
Maintenance of weight loss or stability in subjects with obesity: a retrospective longitudinal analysis of a real-world population
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. …”
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15002
IG feature selection process.
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. …”
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15003
RFE feature selection process.
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. …”
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15004
CICID2017 dataset information.
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. …”
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15005
Shows the basic architecture of an autoencoder.
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. …”
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15006
Architecture of deep neural networks.
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. …”
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15007
Proposed model framework.
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. …”
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15008
WUSTL-EHMS-2020 dataset information.
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. …”
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15009
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15010
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15011
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15012
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15013
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15014
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15015
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15016
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15017
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15018
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15019
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”
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15020
Natural Derivatives of Selective HDAC8 Inhibitors with Potent <i>in Vivo</i> Antitumor Efficacy against Breast Cancer
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. …”