Attributes for causal inference in electronic healthcare databases

Attributes for causal inference in electronic healthcare databases

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...

Full description

Bibliographic Details
Main Authors: Reps, Jenna, Garibaldi, Jonathan M., Aickelin, Uwe, Soria, Daniele, Gibson, Jack E., Hubbard, Richard B.
Format: Conference or Workshop Item
Published: 2013
Subjects:
Biomedical Informatics
Data Mining
Online Access:https://eprints.nottingham.ac.uk/3342/
Description
Summary: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.

Similar Items