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. Author manuscript; available in PMC: 2019 Feb 1.
Published in final edited form as: IEEE Trans Biomed Eng. 2018 Feb;65(2):371–377. doi: 10.1109/TBME.2017.2771468

Table II.

The Number of Clinicians (and Auto-Detection) that are in Agreement (Using Threshold on Kappa Statistic at 0.6) on Normal EEG Patterns that have Majority Consensus

EEG# A R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11
1 5 2 5 2 - 5 1 2 1 5 5 2
3 4 4 - 2 - 4 4 4 2 4 4 4
6 2 7 7 2 - 7 1 7 1 7 7 7
7 7 7 7 2 - 1 2 7 7 7 7 1
11 7 6 6 1 1 6 - 6 1 6 1 2
12 1 6 - 2 - 6 - 6 2 6 6 6
15 1 10 10 10 9 10 10 9 9 10 1 7
17 3 3 6 1 - 3 6 1 6 6 6 6
18 3 3 7 1 - 7 7 7 3 7 7 7
20 7 2 7 1 - 7 7 7 2 7 1 7

AVG 4 5 7 2 5 6 5 6 3 7 5 5

The first column contains identification numbers of EEG the patterns. The second column shows agreement of clinicians with a result from auto-detection algorithm on each EEG pattern. The rest of the columns show agreement of specific clinicians with other results on the same EEG pattern. The last rows in TABLES I and II are the average number of agreement across 10 EEG patterns. These values show on the average how many raters agree with a rater in each column for difficult EEG patterns (TABLE I) and for normal EEG patterns (TABLE II).

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