在韩国使用主动监测数据识别COVID-19疫苗接种后的不良反应:文本挖掘方法
Hye Ah Lee1, Bomi Park2,3, Chung Ho Kim2,3
1Clinical Trial Center, Ewha Womans University Mokdong Hospital, Seoul, Korea.
Epidemiology and health
|July 10, 2025
概括
COVID-19疫苗接种数据的文本挖掘揭示了新的不良反应,如呼吸系统症状和睡眠障碍. 这增强了对疫苗安全性的理解,并改善了监测系统.
科学领域:
- 药物监督 药物监督 药物监督
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
背景情况:
- 疫苗安全监测系统产生有价值的非结构化文本数据.
- 识别以前未报告的不良反应对于加强疫苗安全监测至关重要.
研究的目的:
- 通过使用来自主动监控系统的文本数据,探索2019年新冠肺炎 (COVID-19) 疫苗接种后的不良反应.
- 识别和描述与COVID-19疫苗接种相关的新型不良事件.
主要方法:
- 文本挖掘技术应用于两个调查季节的4,662名参与者的自由文本回复.
- 进行了频率分析,子组分析 (性别,年龄,流感疫苗接种) 和语义网络分析.
主要成果:
- 常见的不良事件 (≥1%) 包括呼吸道症状,睡眠障碍,腰痛和消化不良.
- 发现了影响眼睛,耳朵和口腔的不太常见的不良反应 (≥0.1%至<1.0%).
- 对症状同时出现的分析显示,频繁报告的疾病之间存在显著的关联.
结论:
- 文本挖掘有效地揭示了以前未知的COVID-19疫苗接种不良反应.
- 这些发现扩大了对COVID-19疫苗安全概况的理解.
- 洞察力可以为未来的疫苗安全研究提供信息,并改善监视中的文本数据处理.
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