| アイテムタイプ |
会議発表論文 / Conference Paper(1) |
| 公開日 |
2025-10-07 |
| タイトル |
|
|
タイトル |
Monitoring Over-The-Counter Drug Misuse in Japanese User-Generated Data |
| 言語 |
|
|
言語 |
eng |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Drug Misuse |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Text Classification |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Pharmacovigilance |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Natural Language Processing |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Machine Learning |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Data Visualization |
| 資源タイプ |
|
|
資源タイプ |
conference paper |
| アクセス権 |
|
|
アクセス権 |
open access |
| 著者 |
西山, 智弘
矢田, 竣太郎
若宮, 翔子
Hori, Satoko
荒牧, 英治
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
Introduction: The misuse of over-the-counter (OTC) drugs poses a significant global public health challenge. This study proposes a system for detecting and visualizing inappropriate OTC drug use in social media data. Methods: We constructed a corpus of 20,036 labeled Japanese tweets, including 7,000 medication-related posts, to address the linguistic and cultural nuances. By fine-tuning the Japanese bidirectional encoder representations from transformers models, the system identified misuse patterns such as overuse. The system also incorporates a visualization tool to illustrate temporal and categorical trends, aiding public health authorities in real-time pharmacovigilance efforts. Results: The system demonstrated a strong performance in detecting specific misuse patterns and has the potential to provide insights through the visualization of temporal and categorical trends. Error analysis revealed challenges such as ambiguous terms and noise inherent in social media data. Discussion: The model performed well with sufficient data, but struggled with underrepresented categories. Challenges with ambiguous terms and indirect references emphasize the need for improved contextual understanding and the potential benefits of larger language models or data augmentation techniques. Conclusion: Although this study focused on the Japanese context, the system identified OTC drug misuse patterns and provided information through visualization. This holds promise for real-time pharmacovigilance and can be applied to other languages, contributing to global efforts to monitor and mitigate drug misuse trends. |
| 書誌情報 |
en : Proceedings of the 20th World Congress on Medical and Health Informatics
巻 329,
p. 733-737,
ページ数 5,
発行日 2025-08-19
|
| 会議情報 |
|
|
|
会議名 |
MEDINFO 2025 |
|
|
主催機関 |
Taiwan Association for Medical Informatics (TAMI) |
|
|
開始年 |
2025 |
|
|
開始月 |
08 |
|
|
開始日 |
09 |
|
|
終了年 |
2025 |
|
|
終了月 |
08 |
|
|
終了日 |
13 |
|
|
開催期間 |
2025-08-09 - 2025-08-13 |
|
|
開催地 |
Taipei, Taiwan |
|
開催国 |
TWN |
| 出版者 |
|
|
出版者 |
IOS Press |
| ISSN |
|
|
収録物識別子タイプ |
EISSN |
|
収録物識別子 |
1879-8365 |
| 出版者版DOI |
|
|
関連タイプ |
isReplacedBy |
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.3233/SHTI250937 |
| 出版者版URI |
|
|
関連タイプ |
isReplacedBy |
|
|
識別子タイプ |
URI |
|
|
関連識別子 |
https://ebooks.iospress.nl/doi/10.3233/SHTI250937 |
| 権利 |
|
|
権利情報Resource |
https://creativecommons.org/licenses/by-nc/4.0/ |
|
権利情報 |
© 2025 The Authors. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). |
| 著者版フラグ |
|
|
出版タイプ |
NA |
| 助成情報 |
|
|
|
助成機関名 |
National Center for Global health and Medicine (NCGM) |
|
|
研究課題番号 |
JPJ012425 |
|
|
研究課題名 |
Cross-ministerial Strategic Innovation Promotion Program (SIP) on “Integrated Health Care System” |
| 助成情報 |
|
|
|
助成機関名 |
Japan Science and Technology Agency (JST) |
|
|
研究課題番号 |
JPMJCR20G9 |
|
|
研究課題番号URI |
https://projectdb.jst.go.jp/grant/JST-PROJECT-20218985/ |
|
|
研究課題名 |
医薬品安全性監視のための言語を超えた知識強化情報抽出 |
| 助成情報 |
|
|
|
助成機関名 |
Japan Society for the Promotion of Science (JSPS) |
|
|
研究課題番号 |
JP21H03170 |
|
|
研究課題番号URI |
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21H03170/ |
|
|
研究課題名 |
ソーシャルメディアからの患者の悩み・実践知の抽出技術と活用基盤の確立 |
