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We developed a "PAMD" score which combined the four factors to categorize patients into three risk groups, and the model performed good predictive sensitivity and specificity.
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Cross validations indicated that the LUR model performed well, demonstrating good predictions for sites not used in model calibration and stable coefficients when assessed with the Chow test [ 54].
The derived regression model performed well in predicting spatial patterns of wildfire ignitions at the national level with good accuracy.
The given model performed a good stability and predictability when it was verified by internal and external validation.
Experimental and simulation results show that the air system model performs quite good celerity and accuracy.
It is then possible to answer if the same model performs just as good in other scenarios and hence can be considered generic.
This model performed better, with a good sensitivity of 74% but a poor specificity of 66%.
Both models performed equally good, although the best statistical criteria were obtained with equation (15) which explained more than 97% of the total volume variability with a root mean square error of 13.34 m3 ha−1.
Figure 2 shows the ROC curves as well as AUC for each HMM-based model, indicating that the models 2, 3 and 4 perform good discrimination, whereas the model 1 yields the worst AUC.
The optimal model for imidazopyridine derivatives (Rcv2= 0.776,Rpred2= 0.876) was shown to perform good in prediction accuracy, using GATS2m and BEHe1 descriptors.
perform good at school.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com