Showing 1 - 20 results of 7,890 for search '(((( auc values decrease ) OR ( c values increased ))) OR ( i marked decrease ))', query time: 0.66s Refine Results
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

    ROC curve and AUC value of all models. by Tiago de Oliveira Barreto (20485207)

    Published 2024
    “…As for Specificity (82.94%) and ROC-AUC (82.13%), the Multilayer Perceptron with SGD optimizer obtained the highest scores. …”
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17

    S1 File - by Hongyu Li (1332669)

    Published 2025
    “…Following the overexpression of miRNA 221 in myocardium, there was a marked alleviation of myocardial injury and cardiomyocyte apoptosis and necrosis, significant enhancement of left ventricular systolic function, and marked decrease in the levels of PLB, p-PLB (Ser16), p-PLB (Thr17), caspase 3 and Cyt C, as well as a significant decrease in total calcium levels in myocardium.…”
  18. 18

    Sequential Abbott S/C values. by Neal Alexander (18417)

    Published 2025
    “…Dark blue points, with first S/C ≥0.49, are defined as positive on the first donation, with any increase to the second donation being less than the threshold for fold change. …”
  19. 19
  20. 20

    AUC statistics as calculated from simulated time series. Each statistical metric was calculated within sliding windows, throughout the pre-critical interval. We considered five-, fifteen-, and thirty-day sliding windows. Given that the temperature of the system increased to 12°C on day sixty, we also considered three pre-critical intervals: Days 1 to 60, Days 20 to 60, and Days 30 to 60. To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre by Madeline Jarvis-Cross (22394247)

    Published 2025
    “…To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre</p>…”