Faculty Publications
Mining FDA Resources To Compute Population-Specific Frequencies Of Adverse Drug Reactions
Document Type
Conference
Keywords
ADR, adverse drug reaction, case report, FDA, side-effect
Journal/Book/Conference Title
Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume
2017-January
First Page
1809
Last Page
1814
Abstract
Adverse drug reactions (ADRs) represent one of the main health and economic problems in the world. With increasing data on ADRs, there is an increased need for software tools capable of organizing and storing the information on drug-ADR associations in a form that is easy to use and understand. Here we present a step by step computational procedure capable of extracting drug-ADR frequency data from the large collection of patient safety reports stored in the Federal Drug Administration database. Our procedure is the first of its type capable of generating population specific drug-ADR frequencies. The drug-ADR data generated by our method can be made specific to a single patient population group (such as gender or age) or a single therapy characteristic (such as drug dosage, duration of therapy) or any combination of such.
Department
Department of Computer Science
Original Publication Date
12-15-2017
DOI of published version
10.1109/BIBM.2017.8217935
Repository
UNI ScholarWorks, Rod Library, University of Northern Iowa
Language
en
Recommended Citation
Poleksic, Aleksandar; Turner, Carson; Dalal, Rishabh; Gray, Paul; and Xie, Lei, "Mining FDA Resources To Compute Population-Specific Frequencies Of Adverse Drug Reactions" (2017). Faculty Publications. 809.
https://scholarworks.uni.edu/facpub/809
