@article{ETD,
      school = {M.S.},
      author = {Pacheco, Jennifer},
      url = {http://digitalcollections.ohsu.edu/record/7855},
      title = {Electronic health record phenotyping to facilitate the  categorization of genetic variants of uncertain  significance},
      publisher = {Oregon Health and Science University},
      abstract = {Many genetic variants are of unknown significance (VUS).  Efficient and accurate electronic health record (EHR)  phenotyping, having facilitated genome-wide association  studies, could identify patients with VUSs who exhibit  phenotypic features that might indicate pathogenicity of  those variants. Identifying and following up with these  patients could improve their healthcare, and assist in  improving genetic variant categorization. With further  assessment, these methods, combined with other data, could  be used to identify phenotypes in patients with VUSs, URVs,  or CPVs, which in turn could facilitate the functional  categorization of those variants as either pathogenic or  benign.},
      number = {ETD},
      doi = {https://doi.org/10.6083/7p88cg990},
      recid = {7855},
      address = {2020},
}