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The effects of electronic medical record phenotyping details on genetic association studies: HDL-C as a case study., , , , , and . BioData Min., (2015)Reducing Clinical Noise for Body Mass Index Measures Due to Unit and Transcription Errors in the Electronic Health Record., , , , and . CRI, AMIA, (2017)Mitochondrial Variation and the Risk of Age-Related Macular Degeneration Across Diverse Populations., , , , , and . Pacific Symposium on Biocomputing, page 243-254. (2015)Towards a phenome-wide catalog of human clinical traits impacted by genetic ancestry., , , , , , , and . BioData Min., (2015)Investigating the relationship between mitochondrial genetic variation and cardiovascular-related traits to develop a framework for mitochondrial phenome-wide association studies., , , , , , , and . BioData Min., (2014)Testing Population-Specific Quantitative Trait Associations for Clinical Outcome Relevance in a Biorepository Linked to Electronic Health Records: LPA and Myocardial Infarction in African Americans., , , and . PSB, page 96-107. (2016)Kidney Disease Genetics and the Importance of Diversity in Precision Medicine., , , , and . PSB, page 285-296. (2016)Replication of SCN5A Associations with Electrocardiographic Traits in African Americans from Clinical and Epidemiologic Studies., , , , , , , , , and 11 other author(s). EvoApplications, volume 8602 of Lecture Notes in Computer Science, page 939-951. Springer, (2014)