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Showing 621 - 640 results of 12,978 for search '(( significant ((dangers decrease) OR (larger decrease)) ) OR ( significantly increased decrease ))', query time: 0.52s Refine Results
  1. 621
    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. 622
    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. 623
    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. 624
    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. 625
    Flow chart of participants selection.

    Flow chart of participants selection. by Linjia Duan (13276989)

    Published 2025
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  6. 626
    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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  7. 627
    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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  8. 628
    Baseline characteristics by number of cognitive activities.

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

    Published 2025
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  9. 629
    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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  10. 630
    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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  11. 631
    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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  12. 632
    Robustness check.

    Robustness check. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  13. 633
    Third.

    Third. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  14. 634
    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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  15. 635
    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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  16. 636
    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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  17. 637
    Second.

    Second. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  18. 638
    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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  19. 639
    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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  20. 640
    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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