Author:
Weiss Jeremy C.,Natarajan Sriraam,Peissig Peggy L.,McCarty Catherine A.,Page David
Abstract
Electronic health records (EHRs) are an emerging relational domain with large potential to improve clinical outcomes. We apply two statistical relational learning (SRL) algorithms to the task of predicting primary myocardial infarction. We show that one SRL algorithm, relational functional gradient boosting, outperforms propositional learners particularly in the medically-relevant high recall region. We observe that both SRL algorithms predict outcomes better than their propositional analogs and suggest how our methods can augment current epidemiological practices.
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Cited by
63 articles.
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