Attributes for causal inference in electronic healthcare databases

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Reps, Jenna, Garibaldi, Jonathan M., Aickelin, Uwe, Soria, Daniele, Gibson, Jack E. and Hubbard, Richard B. (2013) Attributes for causal inference in electronic healthcare databases. In: CBMS 2013, The 26th IEEE International Symposium on Computer-Based Medical Systems, Porto, 20-22 June 2013, Porto, Portugal.

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6627871

Abstract

Side effects of prescription drugs present a serious issue.

Existing algorithms that detect side effects generally

require further analysis to confirm causality. In this paper

we investigate attributes based on the Bradford-Hill causality criteria that could be used by a classifying algorithm to definitively identify side effects directly. We found that it would be advantageous to use attributes based on the association strength, temporality and specificity criteria.

Item Type:	Conference or Workshop Item (Paper)
RIS ID:	https://nottingham-repository.worktribe.com/output/1005448
Additional Information:	Published in: 2013 IEEE 26th International Symposium on Computer-Based Medical Systems (CBMS), © IEEE, 2013, doi: 10.1109/CBMS.2013.6627871
Keywords:	Biomedical Informatics, Data Mining
Schools/Departments:	University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User:	Aickelin, Professor Uwe
Date Deposited:	29 Sep 2014 16:18
Last Modified:	04 May 2020 20:20
URI:	https://eprints.nottingham.ac.uk/id/eprint/3342

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