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The three algorithms had excellent performance, as the worst result classified 93.71% of evidences correctly and there is no significant (greater than 1%) difference between the average results, as shown in Table 5.
We did not find the differences between the average results from different cycle days of blood collection from our lab independently from the assays type.
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Because the inter-rater agreement was excellent (c-rho = 0.99 for progastrin and pY-STAT3; and c-rho = 0.98 for p-ERK staining), percentages were reported as the average results between the two readers.
Figure 4 Comparision between the best and the average result found by Tabu Search, CDE-GA and CCE-GA on Polska network.
Figure 8 Comparision between the best and the average result found by Tabu Search, CDE-GA and CCE-GA on TA2 network.
Figure 5 Comparision between the best and the average result found by Tabu Search, CDE-GA and CCE-GA on Germany17 network.
Figure 6 Comparision between the best and the average result found by Tabu Search, CDE-GA and CCE-GA on Atlanta network.
Though there are substantial differences in the average result between small and large hospitals, the difference between the two groups is not significant.
In Fig. 4(a), the images (i), (ii), (iii), (iv) and (v) corresponds to the averaging results between one, three, six, nine and twelve B-frames, respectively.
The difference between the various average results is statistically significant (P-value 2.75 × 10-9 for ANOVA test on the 4 samples of solutions found by each method).
Moreover, statistical analysis indicates that GP consistently outperforms the other methods except SVM using polynomial kernel with degree 2. In fact, as it can be seen in Table 2, the difference between the various average results is statistically significant (P-value 3.05 × 10-5 for ANOVA test on the 4 samples of solutions found by each method).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com