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Adverse drug reactions(ADRs)are undesired effects that occur during normal drug therapy.The daily-increasing ADR reports have brought severe clinical and social problems worldwide.To countermine these ADR-induced problems,efficient detection of possible ADRs in the early drug discovery phage is desired.In this study,we proposed a network model for clinical ADR prediction starting from chemical fingerprints(i.e.,structural fragments of chemicals).