Published on in Vol 12 (2024)
![Data-Driven Identification of Factors That Influence the Quality of Adverse Event Reports: 15-Year Interpretable Machine Learning and Time-Series Analyses of VigiBase and QUEST Data-Driven Identification of Factors That Influence the Quality of Adverse Event Reports: 15-Year Interpretable Machine Learning and Time-Series Analyses of VigiBase and QUEST](https://asset.jmir.pub/assets/5849d31a7a8ee183dd7ff3e0b1b70662.png 480w,https://asset.jmir.pub/assets/5849d31a7a8ee183dd7ff3e0b1b70662.png 960w,https://asset.jmir.pub/assets/5849d31a7a8ee183dd7ff3e0b1b70662.png 1920w,https://asset.jmir.pub/assets/5849d31a7a8ee183dd7ff3e0b1b70662.png 2500w)
1 Centre of Compliance & Quality Control, National Pharmaceutical Regulatory Agency, Petaling Jaya, Malaysia
2 Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan
3 Uppsala Monitoring Centre, Uppsala, Sweden
4 International Center for Health Information Technology, Taipei Medical University, Taipei, Taiwan
5 Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
6 Research Center of Big Data and Meta-Analysis, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
7 School of Gerontology and Long-Term Care, Taipei Medical University, Taipei, Taiwan
*these authors contributed equally