Quantitative data mining in signal detection: the Singapore experience-Reference-Cited by-同舟云学术

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Quantitative data mining in signal detection: the Singapore experience

Published:2020-03-02 Issue:5 Volume:19 Page:633-639
ISSN:1474-0338
Container-title:Expert Opinion on Drug Safety
language:en
Short-container-title:Expert Opinion on Drug Safety

Author:

Chan Cheng Leng¹²,Soh Sally¹,Tan Siew Har¹,Ang Pei San¹,Rudrappa Sowmya¹³,Li Shu Chuen²,Evans Stephen J.W.⁴

Affiliation:

1. Health Products Regulation Group, Health Sciences Authority, Singapore, Singapore

2. School of Biomedical Sciences & Pharmacy, The University of Newcastle, Callaghan, Australia

3. Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore

4. Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom

Publisher

Informa UK Limited

Subject

Pharmacology (medical),General Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/14740338.2020.1734559

Reference8 articles.

1. Data mining for signals in spontaneous reporting databases: proceed with caution

2. Good Signal Detection Practices: Evidence from IMI PROTECT

3. Data mining spontaneous adverse drug event reports for safety signals in Singapore – a comparison of three different disproportionality measures

4. Comparison of Statistical Signal Detection Methods Within and Across Spontaneous Reporting Databases

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Nationwide safety surveillance of COVID-19 mRNA vaccines following primary series and first booster vaccination in Singapore;Vaccine: X;2023-12

2. Comparison of Data Mining Methods for the Signal Detection of Adverse Drug Events with a Hierarchical Structure in Postmarketing Surveillance;Life;2020-08-05

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