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For the evaluation of the agreement, the classification of Landis and Koch[ 13] was used: ICC 0.01-0.20 = slight agreement; 0.21-0.4 = fair; 0.41-0.60 = moderate; 0.61-0.80 = substantial; 0.81-1.0 = almost perfect agreement.
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In assessing agreement, the classifications were applied by individual members of the study team who were not authors of these systems.
This is best exemplified by the modest agreement in the classification of samples (agreement of 64%, kappa score of 0.527, and 95% confidence interval of 0.456 to 0.597) when a cohort of 295 breast cancers was classified into the molecular subtypes by the authors of the original studies on the molecular classification using SSPs by Sorlie's [ 13, 30] and Perou's [ 26, 31] groups.
The agreement between the human reviewer and the computer algorithm had 100% agreement for the classification regression with logistic and linear regression having 94.6% and 92.9% agreement.
Our analyses showed a moderate overall concordance of both, with a high agreement regarding the classification as non-MDS, but with moderate agreement in their classification as MDS.
The interobserver agreement of the classification of the ratio images, i.e., the agreement between two gastroenterologists, was tested using the kappa statistic.
The interobserver agreement of the classification of the ratio images could be an issue; however, in our classification, excellent agreement was observed, with high kappa values.
The rate of agreement on the classification of drusen characteristics between the 2 graders was assessed by calculating the percentage of agreement.
A value less than or equal to 0.40 indicates a poor agreement between the classification categories (Manserud and Leemans 1992).
It shows a good agreement with the classification obtained from k-means cluster with E and log|I| as variables.
We found an excellent inter-observer agreement in the classification of carotid, vertebral and basilar arteries according to the Biffl grading system (K = 0.97).
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