Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49643, first published .
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

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

Sim Mei Choo   1, 2 , MSc ;   Daniele Sartori   3 , MSc ;   Sing Chet Lee   1 , MSc ;   Hsuan-Chia Yang   2, 4, 5, 6 * , PhD ;   Shabbir Syed-Abdul   2, 4, 7 * , MD, PhD

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

Corresponding Author:

  • Shabbir Syed-Abdul, MD, PhD
  • Graduate Institute of Biomedical Informatics
  • Taipei Medical University
  • 301 Yuantong Rd
  • Education & Research Building, 9F, Shuang-Ho Campus
  • Taipei, 235
  • Taiwan
  • Phone: 886 66202589 ext 10930
  • Email: drshabbir@tmu.edu.tw