Development of a Data-Mining Algorithm to Identify Ages at Reproductive Milestones in Electronic Medical Records. - Jennifer Malinowski; Eric Farber-Eger; Dana C. Crawford (Pacific Symposium on Biocomputing, 2014)

Investigating the relationship between mitochondrial genetic variation and cardiovascular-related traits to develop a framework for mitochondrial phenome-wide association studies. - Sabrina L. Mitchell; Jacob B. Hall; Robert J. Goodloe; Jonathan Boston; Eric Farber-Eger; Sarah A. Pendergrass; William S. Bush; Dana C. Crawford (BioData Min., 2014)

Extraction of echocardiographic data from the electronic medical record is a rapid and efficient method for study of cardiac structure and function. - Quinn Stanton Wells; Eric Farber-Eger; Dana C. Crawford (J. Clin. Bioinform., 2014)

The effects of electronic medical record phenotyping details on genetic association studies: HDL-C as a case study. - Logan Dumitrescu; Robert J. Goodloe; Yukiko Bradford; Eric Farber-Eger; Jonathan Boston; Dana C. Crawford (BioData Min., 2015)

Towards a phenome-wide catalog of human clinical traits impacted by genetic ancestry. - Logan Dumitrescu; Nicole A. Restrepo; Robert J. Goodloe; Jonathan Boston; Eric Farber-Eger; Sarah A. Pendergrass; William S. Bush; Dana C. Crawford (BioData Min., 2015)

Searching in the Dark: Phenotyping Diabetic Retinopathy in a De-Identified Electronic Medical Record Sample of African Americans. - Nicole A. Restrepo; Eric Farber-Eger; Dana C. Crawford (CRI, 2016)

Reducing Clinical Noise for Body Mass Index Measures Due to Unit and Transcription Errors in the Electronic Health Record. - Robert J. Goodloe; Eric Farber-Eger; Jonathan Boston; Dana C. Crawford; William S. Bush (CRI, 2017)

Development and Performance of Text-Mining Algorithms to Extract Socioeconomic Status from De-Identified Electronic Health Records. - Brittany M. Hollister; Nicole A. Restrepo; Eric Farber-Eger; Dana C. Crawford; Melinda C. Aldrich; Amy Non (PSB, 2017)

Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort. - Sarah DeLozier; Sarah Bland; Melissa McPheeters; Quinn Stanton Wells; Eric Farber-Eger; Cosmin Adrian Bejan; Daniel Fabbri; S. Trent Rosenbloom; Dan M. Roden; Kevin B. Johnson; Wei-Qi Wei; Josh F. Peterson; et al. (J. Biomed. Informatics, 2021)