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Showing 901 - 920 results of 13,553 for search '(( significant ((green decrease) OR (greater decrease)) ) OR ( significantly increased decrease ))', query time: 0.69s Refine Results
  1. 901
    The influence of training-time noise on classification accuracy and reliability

    The influence of training-time noise on classification accuracy and reliability by Eloy Geenjaar (21533195)

    Published 2025
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  2. 902
    Data sample demographics. Note that AP refers to anti-psychotic medication, and AD refers to anti-depressive medication. Thus, AP and AD in this table refer to the percentage of patients taking anti-psychotic and anti-depressive medication, respectively. PANSS is a symptom scale for schizophrenia. We show its positive, negative, and composite scores.

    Data sample demographics. Note that AP refers to anti-psychotic medication, and AD refers to anti-depressive medication. Thus, AP and AD in this table refer to the percentage of pa... by Eloy Geenjaar (21533195)

    Published 2025
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  3. 903
    An abstract depiction of our model, for the independent version of the model, the context representation is not concatenated inside the local encoder.

    An abstract depiction of our model, for the independent version of the model, the context representation is not concatenated inside the local encoder. by Eloy Geenjaar (21533195)

    Published 2025
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  4. 904
    Associations of number of cognitive activities with all-cause mortality and medication analysis of number of cognitive activities by baseline cognitive function.

    Associations of number of cognitive activities with all-cause mortality and medication analysis of number of cognitive activities by baseline cognitive function. by Linjia Duan (13276989)

    Published 2025
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  5. 905
    These subfigures show a visualization of the context embeddings for the DSVAE model with LS=2=4,CS=2. The first subfigure from the left shows three patient clusters, the second subfigure both patients and controls, the third colors context embeddings based on the subject’s age, and the last subfigure colors the context embeddings based on the subject’s cognitive score, CMINDs.

    These subfigures show a visualization of the context embeddings for the DSVAE model with LS=2=4,CS=2. The first subfigure from the left shows three patient clusters, the second sub... by Eloy Geenjaar (21533195)

    Published 2025
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  6. 906
    The window classification accuracy for two of our proposed models (DSVAE, IDSVAE), windowed FNC (wFNC), and two baseline methods: context-only (CVAE), and local-only (LVAE).

    The window classification accuracy for two of our proposed models (DSVAE, IDSVAE), windowed FNC (wFNC), and two baseline methods: context-only (CVAE), and local-only (LVAE). by Eloy Geenjaar (21533195)

    Published 2025
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  7. 907
    Baseline characteristics by number of cognitive activities.

    Baseline characteristics by number of cognitive activities. by Linjia Duan (13276989)

    Published 2025
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  8. 908
    The three schizophrenia patient clusters visualized using functional connectivity matrices. To create the visualizations, we take all the windows belonging to a cluster and average their wFNC matrix.

    The three schizophrenia patient clusters visualized using functional connectivity matrices. To create the visualizations, we take all the windows belonging to a cluster and average... by Eloy Geenjaar (21533195)

    Published 2025
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  9. 909
    Analysis of FROM dynamics (pre-epidemic).

    Analysis of FROM dynamics (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  10. 910
    Analysis of FROM dynamics (post epidemic).

    Analysis of FROM dynamics (post epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  11. 911
    Robustness check.

    Robustness check. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  12. 912
    Third.

    Third. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  13. 913
    Analysis of TO dynamics (in-epidemic).

    Analysis of TO dynamics (in-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  14. 914
    Analysis of TO dynamics (pre-epidemic).

    Analysis of TO dynamics (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  15. 915
    Descriptive statistical analysis of the total sample.

    Descriptive statistical analysis of the total sample. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  16. 916
    Second.

    Second. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  17. 917
    Dynamics of net spillage in the first stage (pre-epidemic).

    Dynamics of net spillage in the first stage (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  18. 918
    Dynamics of net spillage in the third stage (post epidemic).

    Dynamics of net spillage in the third stage (post epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  19. 919
    Analysis of FROM dynamics (in-epidemic).

    Analysis of FROM dynamics (in-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  20. 920
    Comparison of total overflow for different lag orders.

    Comparison of total overflow for different lag orders. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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