Attributes for causal inference in electronic healthcare databases

Reps, Jenna and Garibaldi, Jonathan M. and Aickelin, Uwe and Soria, Daniele and 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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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: http://eprints.nottingham.ac.uk/id/eprint/3342

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