Sorting Through the Safety Data Haystack: Using Machine Learning to Identify Individual Case Safety Reports in Social-Digital Media-Reference-Cited by-同舟云学术

Sorting Through the Safety Data Haystack: Using Machine Learning to Identify Individual Case Safety Reports in Social-Digital Media

Published:2018-02-14 Issue:6 Volume:41 Page:579-590
ISSN:0114-5916
Container-title:Drug Safety
language:en
Short-container-title:Drug Saf

Author:

Comfort Shaun,Perera Sujan,Hudson Zoe,Dorrell Darren,Meireis Shawman,Nagarajan Meenakshi,Ramakrishnan Cartic,Fine Jennifer

Publisher

Springer Science and Business Media LLC

Subject

Pharmacology (medical),Pharmacology,Toxicology

Link

http://link.springer.com/article/10.1007/s40264-018-0641-7/fulltext.html

Reference39 articles.

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3. Brewer T, Colditz GA. Postmarketing surveillance and adverse drug reactions: current perspectives and future needs. JAMA. 1999;281:824–9.

4. World Health Organization. The importance of pharmacovigilance. 2002. http://apps.who.int/medicinedocs/en/d/Js4893e/ . Accessed 15 Sep 2017.

5. International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. E2B(R3) electronic transmission of individual case safety reports implementation guide—data elements and message specification. 2014. https://www.fda.gov/drugs/guidancecomplianceregulatoryinformation/guidances/ucm274966.htm . Accessed 15 Sep 2017.

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