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Machine Learning Approach for Active Vaccine Safety Monitoring.
Journal of Korean Medical Science ( IF 3.0 ) Pub Date : 2021-08-09 , DOI: 10.3346/jkms.2021.36.e198
Yujeong Kim 1 , Jong Hwan Jang 1 , Namgi Park 2 , Na Young Jeong 3 , Eunsun Lim 3 , Soyun Kim 2 , Nam Kyong Choi 3 , Dukyong Yoon 1, 4
Affiliation  

Vaccine safety surveillance is important because it is related to vaccine hesitancy, which affects vaccination rate. To increase confidence in vaccination, the active monitoring of vaccine adverse events is important. For effective active surveillance, we developed and verified a machine learning-based active surveillance system using national claim data.

中文翻译:

用于主动疫苗安全监测的机器学习方法。

疫苗安全监测很重要,因为它与疫苗犹豫有关,这会影响疫苗接种率。为了增加对疫苗接种的信心,积极监测疫苗不良事件很重要。为了有效的主动监控,我们使用国家索赔数据开发并验证了一个基于机器学习的主动监控系统。
更新日期:2021-08-09
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