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Predicting Adverse Drug Events from Electronic Medical Records.

, , , , and . Foundations of Biomedical Knowledge Representation, volume 9521 of Lecture Notes in Computer Science, Springer, (2015)

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Relational machine learning for electronic health record-driven phenotyping., , , , , , and . J. Biomed. Informatics, (2014)Identifying Adverse Drug Events by Relational Learning., , , , , and . AAAI, page 1599-1605. AAAI Press, (2012)Computational Drug Repositioning Using Continuous Self-Controlled Case Series., , , , , and . KDD, page 491-500. ACM, (2016)Markov logic networks for adverse drug event extraction from text., , , , , , , and . Knowl. Inf. Syst., 51 (2): 435-457 (2017)Predicting Adverse Drug Events from Electronic Medical Records., , , , and . Foundations of Biomedical Knowledge Representation, volume 9521 of Lecture Notes in Computer Science, Springer, (2015)Applying Organizational Network Analysis Techniques to Study Information Use in a Public Health Agency., , , , and . AMIA, AMIA, (2005)Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data., , , , , and . IJCAI, page 2521-2528. IJCAI/AAAI Press, (2016)Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events., , , , , and . ICML, icml.cc / Omnipress, (2012)A case study in use of framework technology as the basis for a software engineering environment., , , , , and . J. Syst. Integr., 4 (3): 195-218 (1994)High-Throughput Machine Learning from Electronic Health Records., , , , , , , and . CoRR, (2019)