Utilizing Deep Learning for Detecting Adverse Drug Events in Structured and Unstructured Regulatory Drug Data Sets-Reference-Cited by-同舟云学术

Utilizing Deep Learning for Detecting Adverse Drug Events in Structured and Unstructured Regulatory Drug Data Sets

Published:2022-07-24 Issue:5 Volume:36 Page:307-317
ISSN:1178-2595
Container-title:Pharmaceutical Medicine
language:en
Short-container-title:Pharm Med

Author:

Knisely Benjamin M.^ORCID,Hatim Qais,Vaughn-Cooke Monifa

Funder

U.S. Food and Drug Administration

Publisher

Springer Science and Business Media LLC

Subject

Pharmacology (medical),Pharmacology

Link

https://link.springer.com/content/pdf/10.1007/s40290-022-00434-y.pdf

Reference47 articles.

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2. Harpaz R, Perez H, Chase HS, Rabadan R, Hripcsak G, Friedman C. Biclustering of adverse drug events in the FDA’s spontaneous reporting system. Clin Pharmacol Ther. 2011;89:243–50.

3. Ly T, Pamer C, Dang O, Brajovic S, Haider S, Botsis T, et al. Evaluation of natural language processing (NLP) systems to annotate drug product labeling with MedDRA terminology. J Biomed Inform. 2018;83:73–86.

4. Spiker J, Kreimeyer K, Dang O, Boxwell D, Chan V, Cheng C, et al. Information visualization platform for postmarket surveillance decision support. Drug Saf. 2020;43:905–15.

5. Karahoca A. Data mining applications in engineering and medicine. London: IntechOpen Limited; 2012.

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