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Reps, Jenna; Garibaldi, Jonathan M.; Aickelin, Uwe; Soria, Daniele; Gibson, Jack E.; Hubbard, Richard B. (2013)
Languages: English
Types: Unknown
Subjects:
Side effects of prescription drugs present a serious issue.\ud Existing algorithms that detect side effects generally\ud require further analysis to confirm causality. In this paper\ud 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.

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