I. Introduction
Clinical phenotypic information comes from actual patient data, which mimics a phenotypic “screen” of the drug effects on human [1]. In this work, we focus on the extraction of the associations between adverse drug reactions (ADRs) and diseases in the clinical phenotypic information contributed by patients themselves in social media. ADR is defined as an appreciably harmful or unpleasant reaction, which results from an intervention related to the use of a medicinal product, predicts hazard from future administration, and warrants prevention or specific treatment, or alteration of the dosage regimen, or withdrawal of the product [2]. ADR represents a significant health problem worldwide and it has been becoming the leading cause of death as well as diseases in United States [3]. A nationwide study in Netherlands demonstrated that 1.83% of hospital admissions are ADR related during 2001 [4]. Therefore, research about ADR is an important topic in healthcare informatics.