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The electronic medical record (EMR) database and the FDA's adverse event reporting system (FAERS) database are the major data sources for mining and testing the ADE associated DDI signals. Most DDI data mining methods focus on pair\u2010wise drug interactions, and methods to detect high\u2010dimensional DDIs in medical databases are lacking. In this paper, we propose 2 novel mixture drug\u2010count response models for detecting high\u2010dimensional drug combinations that induce myopathy. The \u201ccount\u201d indicates the number of drugs in a combination. One model is called fixed probability mixture drug\u2010count response model with a maximum risk threshold (FMDRM\u2010MRT). The other model is called count\u2010dependent probability mixture drug\u2010count response model with a maximum risk threshold (CMDRM\u2010MRT), in which the mixture probability is count dependent. Compared with the previous mixture drug\u2010count response model (MDRM) developed by our group, these 2 new models show a better likelihood in detecting high\u2010dimensional drug combinatory effects on myopathy. CMDRM\u2010MRT identified and validated (54; 374; 637; 442; 131) 2\u2010way to 6\u2010way drug interactions, respectively, which induce myopathy in both EMR and FAERS databases. We further demonstrate FAERS data capture much higher maximum myopathy risk than EMR data do. 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Carolina at Chapel Hill  3103B McGavran\u2010Greenberg Hall, CB #7420 Chapel Hill NC 27599 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Intelligent System and Bioinformatics, College of Automation Harbin Engineering University  NO.145\u20101, Nantong Street, Nangang District Harbin 150001 Heilongjiang China"},{"name":"Center for Computational Biology and Bioinformatics, School of Medicine Indiana University  410 W. 10th St., Suite 5000 Indianapolis IN 46202 USA"},{"name":"Department of Medical and Molecular Genetics, School of Medicine Indiana University  975 West Walnut Street, Medical Research and Library Building, IB 130 Indianapolis 46202 IN USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara K.","family":"Quinney","sequence":"additional","affiliation":[{"name":"Center for Computational Biology and Bioinformatics, School of Medicine Indiana University  410 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