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Conference Paper
Analysis on the Korean Disaster Survivor Interview Dataset Constructed for AI Model Training
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- Authors
- Seung Hun Oh, Dong Hoon Son, Hong Yeon Yu, Sim-Kwon Yoon, Jeong Eun Kim
- Issue Date
- 2024-12
- Citation
- International Conference on Bioinformatics and Biomedicine (BIBM) 2024, pp.7099-7101
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper analyzes the Korean Disaster Survivor Interview (KDSI) Dataset, which was constructed as part of a disaster psychological recovery support service to train AI models for evaluating PTSD (Post-Traumatic Stress Disorder) symptoms among disaster survivors in South Korea. The KDSI dataset encompasses a wide range of information crucial for assessing PTSD symptoms and demonstrates its potential for AI model training. By demonstrating that the performance of AI models trained on well-known foreign PTSD datasets is significantly poor when evaluating PTSD in Korean disaster survivors, this study underscores the importance of using datasets that reflect the linguistic and cultural characteristics of the Korean population for accurate PTSD evaluation.
- KSP Keywords
- Korean population, Post-traumatic stress disorder, South Korea, Support service, wide range