Conferences in Research and Practice in Information Technology
  

Online Version - Last Updated - 20 Jan 2012

 

 
Home
 

 
Procedures and Resources for Authors

 
Information and Resources for Volume Editors
 

 
Orders and Subscriptions
 

 
Published Articles

 
Upcoming Volumes
 

 
Contact Us
 

 
Useful External Links
 

 
CRPIT Site Search
 
    

Drug–drug interactions: A Data Mining Approach

Mammadov, M.

    Drug–drug interaction is one of the important prob- lems of Adverse Drug Reaction (ADR). This presen- tation describes a data mining approach to this prob- lem developed at the University of Ballarat. This approach is based on drug–reaction relationships rep- resented in the form of a vector of weights; each vec- tor related to a particular drug can be considered as a pattern in causing adverse drug reactions. Opti- mal patterns for drugs are determined as a solution to some global optimization problem. Although this approach can be used for solving many ADR prob- lems, we concentrate only on drug–drug interactions. The numerical implementations are carried out on dif- ferent classes of reactions from the Australian Ad- verse Drug Reaction Advisory Committee (ADRAC) database. The results obtained extend our under- standing of the drug–drug interaction from a data mining point of view.
Cite as: Mammadov, M. (2011). Drug–drug interactions: A Data Mining Approach. In Proc. Australasian Data Mining Conference (AusDM 11) Ballarat, Australia. CRPIT, 121. Vamplew, P., Stranieri, A., Ong, K.-L., Christen, P. and Kennedy, P. J. Eds., ACS. 7
pdf (from crpit.com) pdf (local if available) BibTeX EndNote GS