Scott J. Hebbring

Publication Activity (10 Years)

Years Active: 2015-2022
Publications (10 Years): 9

Top Topics

Association Studies

Electronic Health Records

Top Venues

Publications

Andrea H. Ramirez, Lina M. Sulieman, David J. Schlueter, Alese E. Halvorson, Jun Qian, Francis Ratsimbazafy, Roxana Loperena-Cortes, Kelsey R. Mayo, Melissa A. Basford, Nicole Deflaux, Karthik Muthuraman, Karthik Natarajan, Abel N. Kho, Hua Xu, Consuelo H. Wilkins, Hoda Anton-Culver, Eric Boerwinkle, Mine Cicek, Cheryl R. Clark, Elizabeth Cohn, Lucila Ohno-Machado, Sheri D. Schully, Brian K. Ahmedani, Maria Argos, Robert M. Cronin, Christopher J. O'Donnell, Mona Fouad, David B. Goldstein, Philip Greenland, Scott J. Hebbring, Elizabeth W. Karlson, Parinda Khatri, Bruce Korf, Jordan W. Smoller, Stephen Sodeke, John Wilbanks, Justin Hentges, Stephen Mockrin, Christopher Lunt, Stephanie A. Devaney, Kelly Gebo, Joshua C. Denny, Robert J. Carroll, David Glazer, Paul A. Harris, George Hripcsak, Anthony Philippakis, Dan M. Roden
Research Program: Data quality, utility, and diversity. Patterns 3 (8) (2022)
Daehee Kim, Stephanie Gamboa, Vanessa Hernandez, Marlen Martinez-Lopez, Scott J. Hebbring, John Mayer, Jamie Fox
Medical Big Data Analysis System to Discover Associations between Genetic Variants and Diseases. ICC (2021)
Xiayuan Huang, Nicholas Tatonetti, Katie Larow, Brooke Delgoffee, John Mayer, David Page, Scott J. Hebbring
E-Pedigrees: a large-scale automatic family pedigree prediction application. Bioinform. 37 (21) (2021)
Alex Taylor, Ross Kleiman, Scott J. Hebbring, Peggy L. Peissig, David Page
High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records. CoRR (2020)
Xinyuan Zhang, Yogasudha Veturi, Shefali Setia Verma, William Bone, Anurag Verma, Anastasia Lucas, Scott J. Hebbring, Joshua C. Denny, Ian Stanaway, Gail P. Jarvik, David R. Crosslin, Eric B. Larson, Laura Rasmussen-Torvik, Sarah A. Pendergrass, Jordan W. Smoller, Hakon Hakonarson, Patrick Sleiman, Chunhua Weng, David Fasel, Wei-Qi Wei, Iftikhar J. Kullo, Daniel J. Schaid, Wendy K. Chung, Marylyn D. Ritchie
Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43, 870 individuals from the eMERGE network. PSB (2019)
Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg, Zhaobin Kuang, Scott J. Hebbring, Michael D. Caldwell, David Page
High-Throughput Machine Learning from Electronic Health Records. CoRR (2019)
Xiayuan Huang, Robert C. Elston, John Mayer, Zhan Ye, Yuqi He, David Page, Scott J. Hebbring
Use of Electronic Health Record to Predict Family Relationships for Phenome-wide Research. AMIA (2018)
Xiayuan Huang, Robert C. Elston, Guilherme J. Rosa, John Mayer, Zhan Ye, Terrie E. Kitchner, Murray H. Brilliant, David Page, Scott J. Hebbring
Applying family analyses to electronic health records to facilitate genetic research. Bioinform. 34 (4) (2018)
Scott J. Hebbring, Majid Rastegar-Mojarad, Zhan Ye, John Mayer, Crystal Jacobson, Simon M. Lin
Application of clinical text data for phenome-wide association studies (PheWASs). Bioinform. 31 (12) (2015)