TITLE: Leveraging Electronic Health Records for Precision Health
ABSTRACT:Biomedical data science has experienced an explosion of new data over the past decade. Abundant genetic and genomic data are increasingly available in large, diverse data sets due to the maturation of modern molecular technologies. Along with these molecular data, dense, rich phenotypic data are also available on comprehensive clinical data sets from health care provider organizations, clinical trials, population health registries, and epidemiologic studies. The methods and approaches for interrogating these large genetic/genomic and clinical data sets continue to evolve rapidly, as our understanding of the questions and challenges continues to develop. Through applying bioinformatics, statistics, and machine learning approaches to the rich phenotypic data of the EHR, these data can be mined to identify new and interesting patterns of disease expression and relationships. We have been exploring various translational bioinformatics technologies for evaluating the phenomic landscape to improve our understanding of complex traits. These techniques show great promise for the future of precision medicine and precision health.