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nn decrease » a decrease (Expand Search), mean decrease (Expand Search), gy decreased (Expand Search)
e decrease » a decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
50 nn » 50 ns (Expand Search), 50 ng (Expand Search), 50 n (Expand Search)
Showing 1 - 20 results of 49,400 for search '(((( 50 _ decrease ) OR ( _ e decrease ))) OR ( 50 nn decrease ))', query time: 0.70s Refine Results
  1. 1
    Primary endpoint analysis, i.e., time to first occurrence of combined event of 50% decrease in eGFR or ESRD.

    Primary endpoint analysis, i.e., time to first occurrence of combined event of 50% decrease in eGFR or ESRD. by Rozita Mohd (7411322)

    Published 2021
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  2. 2
    Proteasomal activity decreases with ApoE4 expression.

    Proteasomal activity decreases with ApoE4 expression. by Nathan R. Zuniga (20422428)

    Published 2024
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  3. 3
    Expression of ApoB-50 decreased lipid accumulation and inhibited HCV production.

    Expression of ApoB-50 decreased lipid accumulation and inhibited HCV production. by Bei Wang (116772)

    Published 2021
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  4. 4
    Detailed meta–analyses in untreated hypothyroid patients compared with controls for each HRV parameters: RR intervals, SDNN, RMSSD, pNN50, TP, LF, HF, LF/HF.

    Detailed meta–analyses in untreated hypothyroid patients compared with controls for each HRV parameters: RR intervals, SDNN, RMSSD, pNN50, TP, LF, HF, LF/HF. by Valentin Brusseau (12769704)

    Published 2022
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  5. 5
    Clinical characteristics of patients in the increased-, stable-, and decreased-RPR groups.

    Clinical characteristics of patients in the increased-, stable-, and decreased-RPR groups. by Kazuhiko Ikeuchi (9234268)

    Published 2023
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  6. 6
    E<sub>50</sub> values.

    E<sub>50</sub> values. by Junxia Zhou (14381598)

    Published 2024
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  7. 7
    Definitions of the features selected [50].

    Definitions of the features selected [50]. by Yu Zhang (12946)

    Published 2021
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  8. 8
    Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 12 covariates chosen using subjective feature selection.

    Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 12 covariates chosen using subjective feature selection. by Dennis Ochola (11626912)

    Published 2022
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  9. 9
    Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 17 covariates selected after recursive feature selection.

    Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 17 covariates selected after recursive feature selection. by Dennis Ochola (11626912)

    Published 2022
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  10. 10
    E<sub>50</sub> values of angle.

    E<sub>50</sub> values of angle. by Junxia Zhou (14381598)

    Published 2024
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  11. 11
    Curve fitting of E<sub>50</sub>.

    Curve fitting of E<sub>50</sub>. by Junxia Zhou (14381598)

    Published 2024
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  12. 12
    Fitting curves of E<sub>50</sub>.

    Fitting curves of E<sub>50</sub>. by Junxia Zhou (14381598)

    Published 2024
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  13. 13
    E<sub>50</sub> values of size.

    E<sub>50</sub> values of size. by Junxia Zhou (14381598)

    Published 2024
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  14. 14
    E<sub>50</sub> fluctuation coefficient.

    E<sub>50</sub> fluctuation coefficient. by Junxia Zhou (14381598)

    Published 2024
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  15. 15
    Fitting relationship of E<sub>50</sub>.

    Fitting relationship of E<sub>50</sub>. by Junxia Zhou (14381598)

    Published 2024
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  16. 16
    Fitting curve of E<sub>50</sub>.

    Fitting curve of E<sub>50</sub>. by Junxia Zhou (14381598)

    Published 2024
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  17. 17
    Fitting curve of rock E<sub>50</sub>.

    Fitting curve of rock E<sub>50</sub>. by Junxia Zhou (14381598)

    Published 2024
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  18. 18
    Cellular co-infection decreases the potential for superinfection.

    Cellular co-infection decreases the potential for superinfection. by Brigitte E. Martin (8366847)

    Published 2020
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  19. 19
    Characteristics of patients with AKI diagnosed using eKDIGO only by the decrease in sCr (deKDIGO) and no AKI.

    Characteristics of patients with AKI diagnosed using eKDIGO only by the decrease in sCr (deKDIGO) and no AKI. by Marina Wainstein (12437091)

    Published 2022
    “…<p>Characteristics of patients with AKI diagnosed using eKDIGO only by the decrease in sCr (deKDIGO) and no AKI.…”
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  20. 20
    Chronic high glucose induces apoptosis and proteasome activities decrease in INS-1E cells.

    Chronic high glucose induces apoptosis and proteasome activities decrease in INS-1E cells. by Christophe Broca (538652)

    Published 2023
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