Lee, G.; Park, D.; Oh, H. Methodology of Labeling According to 9 Criteria of DSM-5. Applied Sciences 2023, 13, 10481, doi:10.3390/app131810481.
Lee, G.; Park, D.; Oh, H. Methodology of Labeling According to 9 Criteria of DSM-5. Applied Sciences 2023, 13, 10481, doi:10.3390/app131810481.
Lee, G.; Park, D.; Oh, H. Methodology of Labeling According to 9 Criteria of DSM-5. Applied Sciences 2023, 13, 10481, doi:10.3390/app131810481.
Lee, G.; Park, D.; Oh, H. Methodology of Labeling According to 9 Criteria of DSM-5. Applied Sciences 2023, 13, 10481, doi:10.3390/app131810481.
Abstract
Depressive disorder is a disease that causes a decrease in daily function, and the prevalence of depressive disorder in Korea is the highest among OECD countries. However, due to lack of manpower and negative social awareness, timely treatment is not being performed properly. As a solution to this, AI counseling chatbots are emerging, and it is essential to use labeled datasets to create chatbots. Currently, many countries around the world, including Korea, use the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition, DSM-5, but there are no nine labeled datasets according to the DSM-5 depression disorder diagnosis criteria. This study collects sympathetic datasets, analyzes morphemes using Kind Korean Morpheme Analyzer and augments and builds a word dictionary using Word2Vec. As a result, we have labeled the dataset with nine criteria for diagnosing DSM-5 depressive disorder, which will enhance the performance of the counseling chatbot.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
