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Table 1 lists the average accuracy values of our method with the other comparing methods.
For some values of, our method improves the CS performance by 5 : 1 than Elad's method and even 10 : 1 than Duarte-Carvajalino and Sapiro's method for OMP.
The AUROC values of our method using different feature sizes are compared in Supplementary Table S6.
AUC values of our method are higher than those of just using cluster length and heterozygous calls.
Additionally, for this same data set, the recall values of our method outperformed those of any of the other inference methods.
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Finally, we demonstrate the clinical value of our method compared to the state-of-the-art approach in terms of the asymmetry quantification in Alzheimer's disease.
It is remarkable that the maximum value of our method is slightly smaller than that of original one.
The low precision of our estimate of vulture population trend reduces the practical value of our method for monitoring the likely effect on vultures of future changes in diclofenac prevalence to some extent.
The AUC value of our method is 0.71 greater than 0.63 which is the AUC vale of Ligsitecsc.
The increased diagnostic performance found when combining both methods demonstrates the additional value of our method in further improving the diagnostic performance of breast MRI.
This analysis exemplifies the value of our method for the reliable discovery of code variants, even in fragmented DNA from taxonomically divergent organisms.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com