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Tongue Image Database Construction Based on the Expert Opinions: Assessment for Individual Agreement and Methods for
Zhen Qi1, Li-Ping Tu1, Zhi-Yu Luo1
1Basic Medical College, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai 201203, China.
Evidence-Based Complementary and Alternative Medicine : Ecam
|October 30, 2018
Summary
This study introduces a method to evaluate expert agreement in tongue image analysis, improving TCM diagnostic database reliability by selecting consistent raters. The approach enhances interrater agreement, ensuring higher quality expert opinions.
Area of Science:
- Traditional Chinese Medicine (TCM)
- Medical Imaging Analysis
- Biostatistics
Background:
- Reliable diagnostic databases are crucial for Traditional Chinese Medicine (TCM).
- Expert opinion in TCM tongue image analysis requires robust agreement evaluation.
- Identifying and excluding discordant raters is essential for data integrity.
Purpose of the Study:
- To introduce a novel method for individual agreement evaluation to identify discordant raters.
- To optimize expert selection methods for constructing a reliable tongue image database.
- To enhance the overall reliability of TCM diagnostic data based on expert consensus.
Main Methods:
- Fifty TCM experts rated 300 tongue images.
- Gwet's AC1 (first-order agreement coefficient) was used for interrater and intrarater agreement calculation.
- A disagreement score was developed to assess individual expert external consistency.
Main Results:
- The proposed method successfully optimized interrater agreement.
- Method C (intrarater agreement > 0.6 and disagreement score = 0) yielded the highest interrater agreement (0.76 [0.67-0.83]).
- Expert selection significantly improved agreement from 0.53 [0.32-0.75] to 0.76 [0.67-0.83].
Conclusions:
- A comprehensive evaluation considering both internal and external consistency of experts is superior for tongue image database construction.
- The developed method effectively identifies and excludes unreliable raters.
- This approach enhances the quality and reliability of TCM diagnostic databases derived from expert opinions.
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